useful heuristic for problem solving

Heuristic Problem Solving: A comprehensive guide with 5 Examples

What are heuristics, advantages of using heuristic problem solving, disadvantages of using heuristic problem solving, heuristic problem solving examples, frequently asked questions.

• Speed: Heuristics are designed to find solutions quickly, saving time in problem solving tasks. Rather than spending a lot of time analyzing every possible solution, heuristics help to narrow down the options and focus on the most promising ones.
• Flexibility: Heuristics are not rigid, step-by-step procedures. They allow for flexibility and creativity in problem solving, leading to innovative solutions. They encourage thinking outside the box and can generate unexpected and valuable ideas.
• Simplicity: Heuristics are often easy to understand and apply, making them accessible to anyone regardless of their expertise or background. They don’t require specialized knowledge or training, which means they can be used in various contexts and by different people.
• Cost-effective: Because heuristics are simple and efficient, they can save time, money, and effort in finding solutions. They also don’t require expensive software or equipment, making them a cost-effective approach to problem solving.
• Real-world applicability: Heuristics are often based on practical experience and knowledge, making them relevant to real-world situations. They can help solve complex, messy, or ill-defined problems where other problem solving methods may not be practical.
• Potential for errors: Heuristic problem solving relies on generalizations and assumptions, which may lead to errors or incorrect conclusions. This is especially true if the heuristic is not based on a solid understanding of the problem or the underlying principles.
• Limited scope: Heuristic problem solving may only consider a limited number of potential solutions and may not identify the most optimal or effective solution.
• Lack of creativity: Heuristic problem solving may rely on pre-existing solutions or approaches, limiting creativity and innovation in problem-solving.
• Over-reliance: Heuristic problem solving may lead to over-reliance on a specific approach or heuristic, which can be problematic if the heuristic is flawed or ineffective.
• Lack of transparency: Heuristic problem solving may not be transparent or explainable, as the decision-making process may not be explicitly articulated or understood.
• Trial and error: This heuristic involves trying different solutions to a problem and learning from mistakes until a successful solution is found. A software developer encountering a bug in their code may try other solutions and test each one until they find the one that solves the issue.
• Working backward: This heuristic involves starting at the goal and then figuring out what steps are needed to reach that goal. For example, a project manager may begin by setting a project deadline and then work backward to determine the necessary steps and deadlines for each team member to ensure the project is completed on time.
• Breaking a problem into smaller parts: This heuristic involves breaking down a complex problem into smaller, more manageable pieces that can be tackled individually. For example, an HR manager tasked with implementing a new employee benefits program may break the project into smaller parts, such as researching options, getting quotes from vendors, and communicating the unique benefits to employees.
• Using analogies: This heuristic involves finding similarities between a current problem and a similar problem that has been solved before and using the solution to the previous issue to help solve the current one. For example, a salesperson struggling to close a deal may use an analogy to a successful sales pitch they made to help guide their approach to the current pitch.
• Simplifying the problem: This heuristic involves simplifying a complex problem by ignoring details that are not necessary for solving it. This allows the problem solver to focus on the most critical aspects of the problem. For example, a customer service representative dealing with a complex issue may simplify it by breaking it down into smaller components and addressing them individually rather than simultaneously trying to solve the entire problem.

Test your problem-solving skills for free in just a few minutes.

The free problem-solving skills for managers and team leaders helps you understand mistakes that hold you back.

What are the three types of heuristics?

What are the four stages of heuristics in problem solving.

Other Related Blogs

Top 15 Tips for Effective Conflict Mediation at Work

Top 10 games for negotiation skills to make you a better leader, manager effectiveness: a complete guide for managers in 2024, 5 proven ways managers can build collaboration in a team.

Heuristics: Definition, Examples, And How They Work

Benjamin Frimodig

Science Expert

B.A., History and Science, Harvard University

Ben Frimodig is a 2021 graduate of Harvard College, where he studied the History of Science.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

Every day our brains must process and respond to thousands of problems, both large and small, at a moment’s notice. It might even be overwhelming to consider the sheer volume of complex problems we regularly face in need of a quick solution.

While one might wish there was time to methodically and thoughtfully evaluate the fine details of our everyday tasks, the cognitive demands of daily life often make such processing logistically impossible.

Therefore, the brain must develop reliable shortcuts to keep up with the stimulus-rich environments we inhabit. Psychologists refer to these efficient problem-solving techniques as heuristics.

Heuristics can be thought of as general cognitive frameworks humans rely on regularly to reach a solution quickly.

For example, if a student needs to decide what subject she will study at university, her intuition will likely be drawn toward the path that she envisions as most satisfying, practical, and interesting.

She may also think back on her strengths and weaknesses in secondary school or perhaps even write out a pros and cons list to facilitate her choice.

It’s important to note that these heuristics broadly apply to everyday problems, produce sound solutions, and helps simplify otherwise complicated mental tasks. These are the three defining features of a heuristic.

While the concept of heuristics dates back to Ancient Greece (the term is derived from the Greek word for “to discover”), most of the information known today on the subject comes from prominent twentieth-century social scientists.

Herbert Simon’s study of a notion he called “bounded rationality” focused on decision-making under restrictive cognitive conditions, such as limited time and information.

This concept of optimizing an inherently imperfect analysis frames the contemporary study of heuristics and leads many to credit Simon as a foundational figure in the field.

Kahneman’s Theory of Decision Making

The immense contributions of psychologist Daniel Kahneman to our understanding of cognitive problem-solving deserve special attention.

As context for his theory, Kahneman put forward the estimate that an individual makes around 35,000 decisions each day! To reach these resolutions, the mind relies on either “fast” or “slow” thinking.

The fast thinking pathway (system 1) operates mostly unconsciously and aims to reach reliable decisions with as minimal cognitive strain as possible.

While system 1 relies on broad observations and quick evaluative techniques (heuristics!), system 2 (slow thinking) requires conscious, continuous attention to carefully assess the details of a given problem and logically reach a solution.

Given the sheer volume of daily decisions, it’s no surprise that around 98% of problem-solving uses system 1.

Thus, it is crucial that the human mind develops a toolbox of effective, efficient heuristics to support this fast-thinking pathway.

Heuristics vs. Algorithms

Those who’ve studied the psychology of decision-making might notice similarities between heuristics and algorithms. However, remember that these are two distinct modes of cognition.

Heuristics are methods or strategies which often lead to problem solutions but are not guaranteed to succeed.

They can be distinguished from algorithms, which are methods or procedures that will always produce a solution sooner or later.

An algorithm is a step-by-step procedure that can be reliably used to solve a specific problem. While the concept of an algorithm is most commonly used in reference to technology and mathematics, our brains rely on algorithms every day to resolve issues (Kahneman, 2011).

The important thing to remember is that algorithms are a set of mental instructions unique to specific situations, while heuristics are general rules of thumb that can help the mind process and overcome various obstacles.

For example, if you are thoughtfully reading every line of this article, you are using an algorithm.

On the other hand, if you are quickly skimming each section for important information or perhaps focusing only on sections you don’t already understand, you are using a heuristic!

Why Heuristics Are Used

Heuristics usually occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind at the same moment

When studying heuristics, keep in mind both the benefits and unavoidable drawbacks of their application. The ubiquity of these techniques in human society makes such weaknesses especially worthy of evaluation.

More specifically, in expediting decision-making processes, heuristics also predispose us to a number of cognitive biases .

A cognitive bias is an incorrect but pervasive judgment derived from an illogical pattern of cognition. In simple terms, a cognitive bias occurs when one internalizes a subjective perception as a reliable and objective truth.

Heuristics are reliable but imperfect; In the application of broad decision-making “shortcuts” to guide one’s response to specific situations, occasional errors are both inevitable and have the potential to catalyze persistent mistakes.

For example, consider the risks of faulty applications of the representative heuristic discussed above. While the technique encourages one to assign situations into broad categories based on superficial characteristics and one’s past experiences for the sake of cognitive expediency, such thinking is also the basis of stereotypes and discrimination.

In practice, these errors result in the disproportionate favoring of one group and/or the oppression of other groups within a given society.

Indeed, the most impactful research relating to heuristics often centers on the connection between them and systematic discrimination.

The tradeoff between thoughtful rationality and cognitive efficiency encompasses both the benefits and pitfalls of heuristics and represents a foundational concept in psychological research.

When learning about heuristics, keep in mind their relevance to all areas of human interaction. After all, the study of social psychology is intrinsically interdisciplinary.

Many of the most important studies on heuristics relate to flawed decision-making processes in high-stakes fields like law, medicine, and politics.

Researchers often draw on a distinct set of already established heuristics in their analysis. While dozens of unique heuristics have been observed, brief descriptions of those most central to the field are included below:

Availability Heuristic

The availability heuristic describes the tendency to make choices based on information that comes to mind readily.

For example, children of divorced parents are more likely to have pessimistic views towards marriage as adults.

Of important note, this heuristic can also involve assigning more importance to more recently learned information, largely due to the easier recall of such information.

Representativeness Heuristic

This technique allows one to quickly assign probabilities to and predict the outcome of new scenarios using psychological prototypes derived from past experiences.

For example, juries are less likely to convict individuals who are well-groomed and wearing formal attire (under the assumption that stylish, well-kempt individuals typically do not commit crimes).

This is one of the most studied heuristics by social psychologists for its relevance to the development of stereotypes.

Scarcity Heuristic

This method of decision-making is predicated on the perception of less abundant, rarer items as inherently more valuable than more abundant items.

We rely on the scarcity heuristic when we must make a fast selection with incomplete information. For example, a student deciding between two universities may be drawn toward the option with the lower acceptance rate, assuming that this exclusivity indicates a more desirable experience.

The concept of scarcity is central to behavioral economists’ study of consumer behavior (a field that evaluates economics through the lens of human psychology).

Trial and Error

This is the most basic and perhaps frequently cited heuristic. Trial and error can be used to solve a problem that possesses a discrete number of possible solutions and involves simply attempting each possible option until the correct solution is identified.

For example, if an individual was putting together a jigsaw puzzle, he or she would try multiple pieces until locating a proper fit.

This technique is commonly taught in introductory psychology courses due to its simple representation of the central purpose of heuristics: the use of reliable problem-solving frameworks to reduce cognitive load.

Anchoring and Adjustment Heuristic

Anchoring refers to the tendency to formulate expectations relating to new scenarios relative to an already ingrained piece of information.

Put simply, this anchoring one to form reasonable estimations around uncertainties. For example, if asked to estimate the number of days in a year on Mars, many people would first call to mind the fact the Earth’s year is 365 days (the “anchor”) and adjust accordingly.

This tendency can also help explain the observation that ingrained information often hinders the learning of new information, a concept known as retroactive inhibition.

Familiarity Heuristic

This technique can be used to guide actions in cognitively demanding situations by simply reverting to previous behaviors successfully utilized under similar circumstances.

The familiarity heuristic is most useful in unfamiliar, stressful environments.

For example, a job seeker might recall behavioral standards in other high-stakes situations from her past (perhaps an important presentation at university) to guide her behavior in a job interview.

Many psychologists interpret this technique as a slightly more specific variation of the availability heuristic.

How to Make Better Decisions

Heuristics are ingrained cognitive processes utilized by all humans and can lead to various biases.

Both of these statements are established facts. However, this does not mean that the biases that heuristics produce are unavoidable. As the wide-ranging impacts of such biases on societal institutions have become a popular research topic, psychologists have emphasized techniques for reaching more sound, thoughtful and fair decisions in our daily lives.

Ironically, many of these techniques are themselves heuristics!

To focus on the key details of a given problem, one might create a mental list of explicit goals and values. To clearly identify the impacts of choice, one should imagine its impacts one year in the future and from the perspective of all parties involved.

Most importantly, one must gain a mindful understanding of the problem-solving techniques used by our minds and the common mistakes that result. Mindfulness of these flawed yet persistent pathways allows one to quickly identify and remedy the biases (or otherwise flawed thinking) they tend to create!

Further Information

• Shah, A. K., & Oppenheimer, D. M. (2008). Heuristics made easy: an effort-reduction framework. Psychological bulletin, 134(2), 207.
• Marewski, J. N., & Gigerenzer, G. (2012). Heuristic decision making in medicine. Dialogues in clinical neuroscience, 14(1), 77.
• Del Campo, C., Pauser, S., Steiner, E., & Vetschera, R. (2016). Decision making styles and the use of heuristics in decision making. Journal of Business Economics, 86(4), 389-412.

What is a heuristic in psychology?

A heuristic in psychology is a mental shortcut or rule of thumb that simplifies decision-making and problem-solving. Heuristics often speed up the process of finding a satisfactory solution, but they can also lead to cognitive biases.

Bobadilla-Suarez, S., & Love, B. C. (2017, May 29). Fast or Frugal, but Not Both: Decision Heuristics Under Time Pressure. Journal of Experimental Psychology: Learning, Memory, and Cognition .

Bowes, S. M., Ammirati, R. J., Costello, T. H., Basterfield, C., & Lilienfeld, S. O. (2020). Cognitive biases, heuristics, and logical fallacies in clinical practice: A brief field guide for practicing clinicians and supervisors. Professional Psychology: Research and Practice, 51 (5), 435–445.

Dietrich, C. (2010). “Decision Making: Factors that Influence Decision Making, Heuristics Used, and Decision Outcomes.” Inquiries Journal/Student Pulse, 2(02).

Groenewegen, A. (2021, September 1). Kahneman Fast and slow thinking: System 1 and 2 explained by Sue. SUE Behavioral Design. Retrieved March 26, 2022, from https://suebehaviouraldesign.com/kahneman-fast-slow-thinking/

Kahneman, D., Lovallo, D., & Sibony, O. (2011). Before you make that big decision .

Kahneman, D. (2011). Thinking, fast and slow . Macmillan.

Pratkanis, A. (1989). The cognitive representation of attitudes. In A. R. Pratkanis, S. J. Breckler, & A. G. Greenwald (Eds.), Attitude structure and function (pp. 71–98). Hillsdale, NJ: Erlbaum.

Simon, H.A., 1956. Rational choice and the structure of the environment. Psychological Review .

Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185 (4157), 1124–1131.

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

What Are Heuristics?

These mental shortcuts can help people make decisions more efficiently

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Steven Gans, MD is board-certified in psychiatry and is an active supervisor, teacher, and mentor at Massachusetts General Hospital.

Verywell / Cindy Chung 

• History and Origins
• Heuristics vs. Algorithms
• Heuristics and Bias

How to Make Better Decisions

Heuristics are mental shortcuts that allow people to solve problems and make judgments quickly and efficiently. These rule-of-thumb strategies shorten decision-making time and allow people to function without constantly stopping to think about their next course of action.

However, there are both benefits and drawbacks of heuristics. While heuristics are helpful in many situations, they can also lead to  cognitive biases . Becoming aware of this might help you make better and more accurate decisions.

Press Play for Advice On Making Decisions

Hosted by therapist Amy Morin, LCSW, this episode of The Verywell Mind Podcast shares a simple way to make a tough decision. Click below to listen now.

Follow Now : Apple Podcasts / Spotify / Google Podcasts

The History and Origins of Heuristics

Nobel-prize winning economist and cognitive psychologist Herbert Simon originally introduced the concept of heuristics in psychology in the 1950s. He suggested that while people strive to make rational choices, human judgment is subject to cognitive limitations. Purely rational decisions would involve weighing all the potential costs and possible benefits of every alternative.

But people are limited by the amount of time they have to make a choice as well as the amount of information they have at their disposal. Other factors such as overall intelligence and accuracy of perceptions also influence the decision-making process.

During the 1970s, psychologists Amos Tversky and Daniel Kahneman presented their research on cognitive biases. They proposed that these biases influence how people think and the judgments people make.

As a result of these limitations, we are forced to rely on mental shortcuts to help us make sense of the world. Simon's research demonstrated that humans were limited in their ability to make rational decisions, but it was Tversky and Kahneman's work that introduced the study of heuristics and the specific ways of thinking that people rely on to simplify the decision-making process.

How Heuristics Are Used

Heuristics play important roles in both  problem-solving  and  decision-making , as we often turn to these mental shortcuts when we need a quick solution.

Here are a few different theories from psychologists about why we rely on heuristics.

• Attribute substitution : People substitute simpler but related questions in place of more complex and difficult questions.
• Effort reduction : People use heuristics as a type of cognitive laziness to reduce the mental effort required to make choices and decisions.
• Fast and frugal : People use heuristics because they can be fast and correct in certain contexts. Some theories argue that heuristics are actually more accurate than they are biased.

In order to cope with the tremendous amount of information we encounter and to speed up the decision-making process, our brains rely on these mental strategies to simplify things so we don't have to spend endless amounts of time analyzing every detail.

You probably make hundreds or even thousands of decisions every day. What should you have for breakfast? What should you wear today? Should you drive or take the bus? Fortunately, heuristics allow you to make such decisions with relative ease and without a great deal of agonizing.

There are many heuristics examples in everyday life. When trying to decide if you should drive or ride the bus to work, for instance, you might remember that there is road construction along the bus route. You realize that this might slow the bus and cause you to be late for work. So you leave earlier and drive to work on an alternate route.

Heuristics allow you to think through the possible outcomes quickly and arrive at a solution.

Are Heuristics Good or Bad?

Heuristics aren't inherently good or bad, but there are pros and cons to using them to make decisions. While they can help us figure out a solution to a problem faster, they can also lead to inaccurate judgments about other people or situations.

Types of Heuristics

There are many different kinds of heuristics. While each type plays a role in decision-making, they occur during different contexts. Understanding the types can help you better understand which one you are using and when.

Availability

The availability heuristic  involves making decisions based upon how easy it is to bring something to mind. When you are trying to make a decision, you might quickly remember a number of relevant examples. Since these are more readily available in your memory, you will likely judge these outcomes as being more common or frequently occurring.

For example, if you are thinking of flying and suddenly think of a number of recent airline accidents, you might feel like air travel is too dangerous and decide to travel by car instead. Because those examples of air disasters came to mind so easily, the availability heuristic leads you to think that plane crashes are more common than they really are.

Familiarity

The familiarity heuristic refers to how people tend to have more favorable opinions of things, people, or places they've experienced before as opposed to new ones. In fact, given two options, people may choose something they're more familiar with even if the new option provides more benefits.

Representativeness

The representativeness heuristic  involves making a decision by comparing the present situation to the most representative mental prototype. When you are trying to decide if someone is trustworthy, you might compare aspects of the individual to other mental examples you hold.

A soft-spoken older woman might remind you of your grandmother, so you might immediately assume that she is kind, gentle, and trustworthy. However, this is an example of a heuristic bias, as you can't know someone trustworthy based on their age alone.

The affect heuristic involves making choices that are influenced by the emotions that an individual is experiencing at that moment. For example, research has shown that people are more likely to see decisions as having benefits and lower risks when they are in a positive mood. Negative emotions, on the other hand, lead people to focus on the potential downsides of a decision rather than the possible benefits.

The anchoring bias involves the tendency to be overly influenced by the first bit of information we hear or learn. This can make it more difficult to consider other factors and lead to poor choices. For example, anchoring bias can influence how much you are willing to pay for something, causing you to jump at the first offer without shopping around for a better deal.

Scarcity is a principle in heuristics in which we view things that are scarce or less available to us as inherently more valuable. The scarcity heuristic is one often used by marketers to influence people to buy certain products. This is why you'll often see signs that advertise "limited time only" or that tell you to "get yours while supplies last."

Trial and Error

Trial and error is another type of heuristic in which people use a number of different strategies to solve something until they find what works. Examples of this type of heuristic are evident in everyday life. People use trial and error when they're playing video games, finding the fastest driving route to work, and learning to ride a bike (or learning any new skill).

Difference Between Heuristics and Algorithms

Though the terms are often confused, heuristics and algorithms are two distinct terms in psychology.

Algorithms are step-by-step instructions that lead to predictable, reliable outcomes; whereas heuristics are mental shortcuts that are basically best guesses. Algorithms always lead to accurate outcomes, whereas, heuristics do not.

Examples of algorithms include instructions for how to put together a piece of furniture or a recipe for cooking a certain dish. Health professionals also create algorithms or processes to follow in order to determine what type of treatment to use on a patient.

How Heuristics Can Lead to Bias

While heuristics can help us solve problems and speed up our decision-making process, they can introduce errors. As in the examples above, heuristics can lead to inaccurate judgments about how commonly things occur and about how representative certain things may be.

Just because something has worked in the past does not mean that it will work again, and relying on a heuristic can make it difficult to see alternative solutions or come up with new ideas.

Heuristics can also contribute to stereotypes and  prejudice . Because people use mental shortcuts to classify and categorize people, they often overlook more relevant information and create stereotyped categorizations that are not in tune with reality.

While heuristics can be a useful tool, there are ways you can improve your decision-making and avoid cognitive bias at the same time.

We are more likely to make an error in judgment if we are trying to make a decision quickly or are under pressure to do so. Whenever possible, take a few deep breaths . Do something to distract yourself from the decision at hand. When you return to it, you may find you have a fresh perspective, or notice something you didn't before.

Identify the Goal

We tend to focus automatically on what works for us and make decisions that serve our best interest. But take a moment to know what you're trying to achieve. Are there other people who will be affected by this decision? What's best for them? Is there a common goal that can be achieved that will serve all parties?

Process Your Emotions

Fast decision-making is often influenced by emotions from past experiences that bubble to the surface. Is your decision based on facts or emotions? While emotions can be helpful, they may affect decisions in a negative way if they prevent us from seeing the full picture.

Recognize All-or-Nothing Thinking

When making a decision, it's a common tendency to believe you have to pick a single, well-defined path, and there's no going back. In reality, this often isn't the case.

Sometimes there are compromises involving two choices, or a third or fourth option that we didn't even think of at first. Try to recognize the nuances and possibilities of all choices involved, instead of using all-or-nothing thinking .

Rachlin H. Rational thought and rational behavior: A review of bounded rationality: The adaptive toolbox . J Exp Anal Behav . 2003;79(3):409–412. doi:10.1901/jeab.2003.79-409

Shah AK, Oppenheimer DM. Heuristics made easy: An effort-reduction framework . Psychol Bull. 2008;134(2):207-22. doi:10.1037/0033-2909.134.2.207

Marewski JN, Gigerenzer G. Heuristic decision making in medicine .  Dialogues Clin Neurosci . 2012;14(1):77–89. PMID: 22577307

Schwikert SR, Curran T. Familiarity and recollection in heuristic decision making .  J Exp Psychol Gen . 2014;143(6):2341-2365. doi:10.1037/xge0000024

Finucane M, Alhakami A, Slovic P, Johnson S. The affect heuristic in judgments of risks and benefits . J Behav Decis Mak . 2000; 13(1):1-17. doi:10.1002/(SICI)1099-0771(200001/03)13:1<1::AID-BDM333>3.0.CO;2-S

Cheung TT, Kroese FM, Fennis BM, De Ridder DT. Put a limit on it: The protective effects of scarcity heuristics when self-control is low . Health Psychol Open . 2015;2(2):2055102915615046. doi:10.1177/2055102915615046

Mohr H, Zwosta K, Markovic D, Bitzer S, Wolfensteller U, Ruge H. Deterministic response strategies in a trial-and-error learning task . Inman C, ed. PLoS Comput Biol. 2018;14(11):e1006621. doi:10.1371/journal.pcbi.1006621

Lang JM, Ford JD, Fitzgerald MM.  An algorithm for determining use of trauma-focused cognitive-behavioral therapy .  Psychotherapy   (Chic) . 2010;47(4):554-69. doi:10.1037/a0021184

Bigler RS, Clark C. The inherence heuristic: A key theoretical addition to understanding social stereotyping and prejudice. Behav Brain Sci . 2014;37(5):483-4. doi:10.1017/S0140525X1300366X

del Campo C, Pauser S, Steiner E, et al.  Decision making styles and the use of heuristics in decision making .  J Bus Econ.  2016;86:389–412. doi:10.1007/s11573-016-0811-y

Marewski JN, Gigerenzer G. Heuristic decision making in medicine .  Dialogues Clin Neurosci . 2012;14(1):77-89. doi:10.31887/DCNS.2012.14.1/jmarewski

Zheng Y, Yang Z, Jin C, Qi Y, Liu X. The influence of emotion on fairness-related decision making: A critical review of theories and evidence .  Front Psychol . 2017;8:1592. doi:10.3389/fpsyg.2017.01592

Bazerman MH. Judgment and decision making. In: Biswas-Diener R, Diener E, eds.,  Noba Textbook Series: Psychology.  DEF Publishers.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Ohio State nav bar

The Ohio State University

• BuckeyeLink
• Find People
• Search Ohio State

Some Helpful Problem-Solving Heuristics

A  heuristic  is a thinking strategy, something that can be used to tease out further information about a problem and thus help you figure out what to do when you don’t know what to do. Here are 25 heuristics that can be useful in solving problems. They help you monitor your thought processes, to step back and watch yourself at work, and thus keep your cool in a challenging situation.

• Ask somebody else  how to do the problem. This strategy is probably the most used world-wide, though it is not one we encourage our students to use, at least not initially.
• Guess and try  (guess, check, and revise). Your first guess might be right! But incorrect guesses can often suggest a direction toward a solution. (N.B. A spreadsheet is a powerful aid in guessing and trying. Set up the relationships and plug in a number to see if you get what you want. If you don’t, it is easy to try another number. And another.)
• Restate the problem  using words that make sense to you. One way to do this is to explain the problem to someone else. Often this is all it takes for the light to dawn.
• Organize information  into a table or chart. Having it laid out clearly in front of you frees up your mind for thinking. And perhaps you can use the organized data to generate more information.
• Draw a picture  of the problem. Translate problem information into pictures, diagrams, sketches, glyphs, arrows, or some other kind of representation.
• Make a model  of the problem. The model might be a physical or mental model, perhaps using a computer. You might vary the problem information to see whether and how the model may be affected.
• Look for patterns , any kind of patterns: number patterns, verbal patterns, spatial/visual patterns, patterns in time, patterns in sound. (Some people define mathematics as the science of patterns.)
• Act out the problem , if it is stated in a narrative form. Acting it out can have the same effect as drawing a picture. What’s more, acting out the problem might disclose incorrect assumptions you are making.
• Invent notation . Name things in the problem (known or unknown) using words or symbols, including relationships between problem components.
• Write equations . An equation is simply the same thing named two different ways.
• Check all possibilities  in a systematic way. A table or chart may help you to be systematic.
• Work backwards  from the end condition to the beginning condition. Working backwards is particularly helpful when letting a variable (letter) represent an unknown.
• Identify subgoals  in the problem. Break up the problem into a sequence of smaller problems (“If I knew this, then I could get that”).
• Simplify the problem . Use easier or smaller numbers, or look at extreme cases (e.g., use the minimum or maximum value of one of the varying quantities).
• Restate the problem again . After working on the problem for a time, back off a bit and put it into your own words in still a different way, since now you know more about it.
• Change your point of view . Use your imagination to change the way you are looking at the problem. Turn it upside down, or pull it inside out.
• Check for hidden assumptions  you may be making (you might be making the problem harder than it really is). These assumptions are often found by changing the given numbers or conditions and looking to see what happens.
• Identify needed and given information clearly . You may not need to find everything you think you need to find, for instance.
• Make up your own technique . It is your mind, after all; use mental actions that make sense to you. The key is to do something that engages you with the problem.
• Try combinations of the above heuristics .

These heuristics can be readily pointed out to students as they engage problems in the classroom. However, real-world problems are often confronted many times over or on increasingly complex levels. For those kinds of problems, George Polya, the father of modern problem-solving heuristics, identified a fifth class (E) of looking-back heuristics. We include these here for completeness, but also with the teaching caveat that solutions often improve and insights grow deeper after the initial pressure to produce a solution has been resolved. Subsequent considerations of a problem situation are invariably deeper than the first attempt.

• Check your solution . Substitute your answer or results back into the problem. Are all of the conditions satisfied?
• Find another solution . There may be more than one answer. Make sure you have them all.
• Solve the problem a different way . Your first solution will seldom be the best solution. Now that the pressure is off, you may readily find other ways to solve the problem.
• Solve a related problem . Steve Brown and Marion Walter in their book,  The Art of Problem Posing , suggest the “What if not?” technique. What if the train goes at a different speed? What if there are 8 children, instead of 9? What if . . .? Fascinating discoveries can be made in this way, leading to:
• Generalize the solution . Can you glean from your solution how it can be made to fit a whole class of related situations? Can you prove your result?

Table of Contents

Heuristics are mental shortcut techniques used to solve problems and make decisions efficiently. These techniques are used to reduce the decision making time and allow the individual to function without interrupting their next course of action.

What Is Heuristics?

Heuristics are a time-saving approach to solving problems and making decisions efficiently. Heuristics processes are usually used to find quick answers and solutions to problems. However, decisions based on this mindset are not always accurate. They serve as quick mental references that are used for everyday problems and experiences.

Humans and animals resort to this mindset because processing every information that comes into the brain takes time and effort. With the help of these shortcut techniques, the brain can make faster and efficient decisions despite the consequences. This is known as the accuracy effort trade-off theory. This theory works because not every decision requires the same amount of time and energy.

Hence, people use it as a means to save time. Another reason why people resort to heuristics is that the brain simply doesn’t have the capacity to process everything and so they must resort to these mental shortcuts to make quick decisions. A 2014 study 1 Mousavi, S., & Gigerenzer, G. (2014). Risk, uncertainty, and heuristics.  Journal of Business Research ,  67 (8), 1671-1678.  https://doi.org/10.1016/j.jbusres.2014.02.013 demonstrated that in case of uncertainty and a lack of information, heuristics allows a “less is more effect” wherein less information leads to more accuracy. It is worth mentioning that the applicability and usefulness of heuristics depend on the situation.

A 2011 study 2 Gigerenzer G, Gaissmaier W. Heuristic decision making. Annu Rev Psychol. 2011;62:451-82. doi: 10.1146/annurev-psych-120709-145346. PMID: 21126183. pointed out that there may be two reasons for relying on heuristics. They are:

• Individuals and organizations often rely on simple heuristics in an adaptive way
• Ignoring part of the information can lead to more accurate judgments than weighing and adding all information

Although heuristics are useful, sometimes they can be inaccurate. In case an individual relies on it too heavily, it may result in incorrect judgments or cognitive biases. Understanding commonly unfavorable heuristics and identifying situations that may affect behavior can help individuals avoid mental pitfalls. It is important to assess major problems by making a list of pros and cons. In order to avoid inaccurate decisions, you can consult trusted individuals, take time to think through things where quick decisions may cause significant problems such as catching an important flight. Hence, it is important to be mindful of the information that is being processed in the brain to make accurate decisions.

History Of Heuristics

Nobel prize-winning psychologist, Herbert Simon suggested that although people attempt to make rational decisions, humans are subject to cognitive limitations. A 2013 study 3 Rachlin, H. (2003). Rational thought and rational behavior: A review of bounded rationality: The adaptive toolbox. Journal of the Experimental Analysis of Behavior, 79(3), 409-412. https://doi.org/10.1901/jeab.2003.79-409 pointed out that rational decisions involve weighing different factors such as potential costs against potential benefits. People are often limited by time to make choices as well as the amount of information we have at our disposal. Other factors that influence our thinking are overall intelligence and accuracy of perceptions.

Psychologists Amos Tversky and Daniel Kahneman proposed that cognitive biases influence how people think and the judgements people make about events. Due to these limitations, we are often forced to rely on our instinctive shortcuts i.e heuristics to make sense of the world. Simon’s research indicated that humans have a limited ability to make rational decisions. On the other hand, Tversky and Kahneman’s research 4 Kahneman, D., & Tversky, A. (1977). Prospect theory. An analysis of decision making under risk. https://doi.org/10.21236/ada045771 represented how people have specific ways to simplify the decision-making process.

Types Of Heuristics

Some of the common heuristics may include the following:

1. Availability Heuristics

This involves making decisions based on the information that is readily available in one’s mind. When an individual makes a decision, they immediately refer to a number of relevant examples. Since the relevant information is readily available in their memory, they are more likely to conclude that these outcomes are common. For example, dramatic, violent deaths are usually more highly publicized and hence have higher availability.

Another instance where availability heuristics may work is if an individual is thinking about taking a trip and thinks of a number of recent airline accidents. This may lead them to think that air travel is dangerous. This may also enable them to resort to traveling by car instead. Since airline disasters came to their mind easily, the availability heuristics lead them to think that plane crashes are more common even though it may not be entirely true.

2. Representative Heuristics

This involves making a decision based on the comparison of the present situation and the most relevant mental prototype. In case an individual is trying to decide if someone is trustworthy they may compare the incident with other mental examples. For instance, an older woman sitting beside you at a train station may remind you of your grandmother. You may immediately assume that she may be kind, gentle, and trustworthy. People tend to believe in the existing mental information since the traits match up to the individual’s mental prototype.

3. Affect Heuristics

This involves making choices that are influenced by emotions that an individual is experiencing at that moment. Research 5 Finucane, M. L., Alhakami, A., Slovic, P., & Johnson, S. M. (2000). The affect heuristic in judgments of risks and benefits. Journal of Behavioral Decision Making, 13(1), 1-17. https://doi.org/10.1002/(sici)1099-0771(200001/03)13:1<1::aid-bdm333>3.0.co;2-s has demonstrated that people are more likely to view decisions as having benefits and lower risks when their mood is positive. However, negative emotions lead people to focus on the potential downfall of a decision rather than the possible benefits.

4. Satisficing Heuristics

This is a decision making strategy wherein the first option that fulfills the criteria is selected even if there are better alternatives available. Hebert Simon formulated the concept of satisficing. This theory 6 Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99. https://doi.org/10.2307/1884852 is used to choose one alternative from a set of alternatives in situations of uncertainty. In this case, uncertainty refers to the total set of alternatives and their consequences that cannot be known or foreseen. For instance, professional real estate entrepreneurs rely on this theory to decide where they should invest to develop new commercial areas. Although there may be better alternatives available, they resort to the first option that fulfills their criteria.

Advantages Of Heuristics

Some of the most common advantages of using this cognitive approach are:

• Facilitates timely decisions
• Makes decision making simpler
• Less information, more accuracy
• Quick answers to problems
• Reduces complex information into simple and manageable set of choices
• Frees up cognitive resources for more complex planning

Heuristics & Cognitive Bias

Although heuristics can advance our problems and decision-making process, it can even cause errors. It can often lead to inaccurate judgments based on how common things can occur and how certain events influence our decisions. It is important to realize that even though something worked in the past, it doesn’t necessarily mean that it will work again. Relying on existing heuristics can make it difficult to see alternatives or brainstorm new ideas. A 2014 study pointed out that heuristics can also contribute to other things such as stereotypes and prejudice. Due to this people often overlook more relevant information and create stereotypical categorization that is not entirely true.

Read More About Cognitive Bias Here

Making Quick Decisions With Heuristics

Heuristics allow us to make quick decisions and make our life easier. It is often accurate. However, it is important to be aware of what is influencing our decisions in order to avoid potential cognitive biases. This will allow us to make more accurate decisions.

Heuristics At A Glance

• Heuristics are mental shortcut techniques used to solve problems and make decisions efficiently.
• Heuristics processes are usually used to find quick answers and solutions to problems.
• They serve as quick mental references that are used for everyday problems and experiences.
• With the help of these shortcut techniques, the brain can make faster and efficient decisions despite the consequences.
• Sometimes it may result in incorrect judgments or cognitive biases.
• It is important to be aware of what is influencing our decisions in order to avoid potential cognitive biases.

References:

• 1 Mousavi, S., & Gigerenzer, G. (2014). Risk, uncertainty, and heuristics.  Journal of Business Research ,  67 (8), 1671-1678.  https://doi.org/10.1016/j.jbusres.2014.02.013
• 2 Gigerenzer G, Gaissmaier W. Heuristic decision making. Annu Rev Psychol. 2011;62:451-82. doi: 10.1146/annurev-psych-120709-145346. PMID: 21126183.
• 3 Rachlin, H. (2003). Rational thought and rational behavior: A review of bounded rationality: The adaptive toolbox. Journal of the Experimental Analysis of Behavior, 79(3), 409-412. https://doi.org/10.1901/jeab.2003.79-409
• 4 Kahneman, D., & Tversky, A. (1977). Prospect theory. An analysis of decision making under risk. https://doi.org/10.21236/ada045771
• 5 Finucane, M. L., Alhakami, A., Slovic, P., & Johnson, S. M. (2000). The affect heuristic in judgments of risks and benefits. Journal of Behavioral Decision Making, 13(1), 1-17. https://doi.org/10.1002/(sici)1099-0771(200001/03)13:1<1::aid-bdm333>3.0.co;2-s
• 6 Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99. https://doi.org/10.2307/1884852

Mental Health Topics (A-Z)

• Abrasive Personality
• Academic Problems And Skills
• Actor-Observer Bias
• Addiction And The Brain
• Causes Of Addiction
• Complications Of Addiction
• Stages Of Addiction
• Types Of Addiction
• Adjustment Disorder
• Adverse Childhood Experiences
• Premature Aging
• Aging And Mental Health
• Agoraphobia
• Agreeableness
• Alcohol Use Disorder
• Alcohol Withdrawal
• Alcohol And Mental Health
• End Stage Alcoholism
• Treatment For Alcoholism
• Alienation  
• Alzheimer’s Disease
• Anger Management
• Animal Behavior
• Treatment For Anorexia Nervosa
• Anthropomorphism
• Anthropophobia
• Antidepressants
• Arachnophobia
• Art Therapy
• Causes Of Asperger’s Syndrome
• Coping With Asperger Syndrome
• Symptoms Of Asperger’s Syndrome
• Treatment For Asperger’s Syndrome
• Astraphobia
• Attachment styles
• Attachment Theory
• Attention Deficit Hyperactivity Disorder (ADHD)
• Avoidant Personality Disorder
• Bathophobia
• Behavioral Change
• Behavioral Economics
• Bereavement
• Body-Focused Repetitive Behaviors (BFRB)
• Bibliophobia
• Bibliotherapy
• Big 5 Personality Traits  
• Binge Drinking
• Binge Eating Disorder
• Binge Watching
• Causes Of Bipolar Disorder
• Treatment of Bipolar Disorder
• Birthday Depression
• Body language
• Borderline Personality Disorder (BPD)
• Causes Of Boredom
• How To Improve Brain Health
• Nutrition And Brain Health
• Brain Science
• Bulimia Nervosa
• Causes Of Burnout
• The Bystander Effect
• Caffeine Use Disorder 
• Capgras Delusion
• Caregiving  
• Character Traits 
• Child Development  
• Child Discipline 
• Christmas And Mental Health  
• Types Of Chronic Pain
• Chronomentrophobia  
• City Syndromes
• Traits Of Cluster B Personality Disorder
• Cluster B Personality Disorders Treatment 
• Coping With Codependency 
• Effectiveness Of Cognitive-Behavioral Therapy (CBT) 
• Types of Cognitive Biases
• Cognitive Decline
• Cognitive Dissonance  
• Color Psychology
• Commitment Phobia
• Communication Disorders 
• Compassion Fatigue 
• Compulsive Buying Disorder
• Conduct Disorder
• Confirmation Bias  
• Conscientiousness
• Consumer Behavior  
• Consumerism  
• Couples Therapy
• Decision-making
• Default Mode Network (DMN) And Alzheimer’s Disease
• Defense Mechanisms
• Delusional Disorder
• Dependent Personality Disorder
• Depression 
• Depression At Night
• Dermatillomania
• Discrimination
• Disruptive Mood Dysregulation Disorder (DMDD)
• Dissociative Disorders
• Treatment Of Dissociative Fugue
• Dissociative Identity Disorder
• Dissociative Trance Disorder
• Domestic Violence and Mental Health
• Dopamine Deficiency
• How To Increase Dopamine
• Dream Interpretation
• Drug Abuse  
• Drunkorexia
• Coping With The Dunning-Kruger Effect
• Types of Dysgraphia 
• Dyspareunia
• Dysthymia (Persistent Depressive Disorder)
• Causes Of Eating Disorders
• Self Help Strategies For Eating Disorders
• Treatment For Eating Disorders
• Ego Depletion
• Embarrassment
• Emotional Regulation
• Emotional Abuse  
• Improving Emotional Intelligence (EI)
• Empathic Accuracy
• Environmental Psychology 
• Evolutionary Psychology
• Executive Function
• Exhibitionistic Disorder
• Expressive Language Disorder
• Signs Of An Extrovert
• False Memory
• Types of Family Dynamics
• Fear of Missing Out (FOMO)
• Financial Therapy  
• First Impression
• Forensic Psychology 
• Four Pillars Of Mental Health
• Free Will  
• Freudian Psychology
• Friends And Mental Health  
• Gambling Disorder
• Ganser Syndrome
• Gaslighting
• Gender Dysphoria
• Gender and Alienation 
• Gender Bias 
• Causes Of Generalized Anxiety Disorder (GAD)
• Coping With Generalized Anxiety Disorder (GAD)
• Symptoms Of Generalized Anxiety Disorder (GAD)
• Generalized Anxiety Disorder Treatment
• Geographical Psychology  
• Gerascophobia
• Geriatric Depression
• Group Therapy
• Growth Mindset
• How To Strengthen Your Gut Feeling
• How To Form Effective Habits
• Hakomi Therapy
• Halo Effect
•  Healing From Trauma
• Heliophobia
• Hexaco Personality Test
• Highly Sensitive Person (HSP)
• Histrionic Personality Disorder
• Hoarding Disorder
• Holiday Depression
• Holiday Stress  
• Types Of Holistic Health Treatments
• Homelessness and Mental Health
• Homosexuality
• Horn Effect
• Human Trafficking And Mental Health
• Hypersomnia
• Illness Anxiety Disorder
• Imagination
• Impostor Syndrome
• Impulse Buying
• Impulse Control Disorder (ICD)
• Inspiration
• Intellectual Disability
• Internet Addiction
• Introversion
• Kleptomania
• Laughter Therapy
• Learned Helplessness
• Life Satisfaction 
• Types Of Life Skills
• Living With Someone With Mental Illness
• Locus Of Control
• How To Practice Healthy Love In Relationships
• Love Addiction
• Love And Relationships  
• Love And Mental Health
• Self Love Deficit Disorder
• Triangular Theory Of Love
• Machiavellianism
• Mageirocophobia
• Benefits Of Magical Thinking
• Magical Thinking OCD
• Causes Of Depression
• Coping With Depression
• Treatment For Depression
• Types Of Depression
• Maladaptive Daydreaming
• Manic Depression
• Manic Episode
• Mens Mental Health 
• Mental Exercises
•  Mental Health And Holidays 
• Children’s Mental Health Awareness
• Mental Health Disability
• Mental Illness 
• Mental Wellness In New Year 
• Metacognition
• Microaggression
• Microexpressions
• Midlife Crisis 
• Mindfulness
• Money and Mental Health
• Mood Disorders
• Motivated Reasoning
• Music and Mental Health
• Music Therapy
• Myers-Briggs Type Indicator (MBTI)
• Nature and Mental Health
• Necrophobia
• Neuroticism
• Night Eating Syndrome
• Causes Of Nightmare Disorder
• Treatment for Nightmare Disorder
• Nyctophobia
• Obsessive-Compulsive Disorder (OCD)
• Obsessive Love Disorder
• Online Counseling
• Online Therapy
• Onychophagia (Nail Biting)
• Oppositional Defiant Disorder (ODD)
• Panic Disorder
• Panic Disorder with Agoraphobia  
• Causes Of Paranoia
• Coping With Paranoia
• Helping Someone With Paranoia
• Symptoms Of Paranoia
• Treatment Of Paranoia
• Types Of Paranoia
• Paranoid Personality Disorder
• Coping With Paranoid Schizophrenia
• Helping Someone With Paranoid Schizophrenia
• Treatment of Paranoid Schizophrenia
• Parental Alienation Syndrome  
• Parkinson’s Disease
• Passive Aggression
• Pathological Jealousy
• Perfectionism
• Performance Anxiety
• Perinatal Mood And Anxiety Disorders (PMADs)
• Personality
• Personality Disorders
• Pet Therapy
• Pica Disorder
• Positive Psychology
• Causes Of PTSD
• Post-Traumatic Stress Disorder in Children
• Coping With Post-Traumatic Stress Disorder (PTSD)
• Diagnosis Of Post-Traumatic Stress Disorder (PTSD)
• Symptoms Of Post-Traumatic Stress Disorder (PTSD)
• Treatment Of Post-Traumatic Stress Disorder (PTSD)
• Treatment Of Postpartum Depression
• Postpartum Psychosis
• Premature Ejaculation
• Procrastination
• Psychoanalysis
• The Psychology Behind Smoking
• Psychotherapy
• Psychotic Depression
• Reactive Attachment Disorder
• Recovered Memory Syndrome
• Rejection Sensitive Dysphoria
• Relationships
• Reminiscence Therapy
• Repetitive Self-Mutilation
• Restless Legs Syndrome
• Retrograde Amnesia
• Rumination Disorder
• Seasonal Affective Disorder (SAD)
• Schema Therapy
• Childhood Schizophrenia
• Hebephrenia (Disorganized Schizophrenia)
• Treatment Of Schizophrenia
• Schizophrenia Spectrum Disorder 
• Selective Mutism
• Self-Actualization
• Self Care And Wellness
• Self-Control
• Self-disclosure
• Self-Esteem
• Self-Monitoring
• Self-motivation
• Self-Serving Bias
• Sensory Processing Disorder
• Separation Anxiety Disorder
• Separation Anxiety in Relationships
• Serial Killers
• Sexual Masochism Disorder
• Sexual Orientation
• Shared Psychotic Disorder
• Signs And Symptoms Of Schizophrenia
• Situational Stress
• Situationship
• Non-Rapid Eye Movement (NREM) Sleep Arousal Disorders
• Parasomnias
• Sleep Disorders
• Sleep Paralysis
• Sleeplessness
• Sleep Meditation
• Sociability
• Social Anxiety Disorder
• Social Media Addiction
• Social Media And Mental Health
• Somatic Symptom Disorder ( SSD )
• Specific Reading Comprehension Deficit
• Spirituality
• Stage Fright
• Stendhal Syndrome
• Stereotypes
• Acute Stress Disorder
• Stress Management
• Suicide And Mental Health  
• Suicide Grief 
• Teen Dating Violence
• Time Management Techniques
• 10 Helpful Time Management Tips
• Tobacco-Related Disorders
• Toxic Love Disorder 
• Transgender
• Transient Tic Disorder
• Trauma and Addiction
• Trichotillomania
• Venustraphobia
• Video Game Addiction
• Virtual Reality and Mental Health
• Voyeuristic Disorder
• Weight Watchers
• Werther Syndrome
• Good Mental Health
• Stockholm Syndrome
• Work and Mental Health 
• How To Cure Workaholism
• Workplace Bullying
• Workplace Stress
• Yoga For Mental Health
• Young Male Syndrome
• Zeigarnik Effect
• Zone of Proximal Development  

Copyright 2024

If you're seeing this message, it means we're having trouble loading external resources on our website.

If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked.

To log in and use all the features of Khan Academy, please enable JavaScript in your browser.

AP®︎/College Computer Science Principles

Course: ap®︎/college computer science principles   >   unit 4, using heuristics.

• Undecidable problems
• Solving hard problems

Traveling Salesperson Problem

The brute force approach, developing a heuristic, the nearest-neighbor heuristic, heuristics everywhere, want to join the conversation.

• Upvote Button navigates to signup page
• Downvote Button navigates to signup page
• Flag Button navigates to signup page

7.3 Problem-Solving

Learning objectives.

By the end of this section, you will be able to:

• Describe problem solving strategies
• Define algorithm and heuristic
• Explain some common roadblocks to effective problem solving

   People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

The study of human and animal problem solving processes has provided much insight toward the understanding of our conscious experience and led to advancements in computer science and artificial intelligence. Essentially much of cognitive science today represents studies of how we consciously and unconsciously make decisions and solve problems. For instance, when encountered with a large amount of information, how do we go about making decisions about the most efficient way of sorting and analyzing all the information in order to find what you are looking for as in visual search paradigms in cognitive psychology. Or in a situation where a piece of machinery is not working properly, how do we go about organizing how to address the issue and understand what the cause of the problem might be. How do we sort the procedures that will be needed and focus attention on what is important in order to solve problems efficiently. Within this section we will discuss some of these issues and examine processes related to human, animal and computer problem solving.

PROBLEM-SOLVING STRATEGIES

   When people are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

Problems themselves can be classified into two different categories known as ill-defined and well-defined problems (Schacter, 2009). Ill-defined problems represent issues that do not have clear goals, solution paths, or expected solutions whereas well-defined problems have specific goals, clearly defined solutions, and clear expected solutions. Problem solving often incorporates pragmatics (logical reasoning) and semantics (interpretation of meanings behind the problem), and also in many cases require abstract thinking and creativity in order to find novel solutions. Within psychology, problem solving refers to a motivational drive for reading a definite “goal” from a present situation or condition that is either not moving toward that goal, is distant from it, or requires more complex logical analysis for finding a missing description of conditions or steps toward that goal. Processes relating to problem solving include problem finding also known as problem analysis, problem shaping where the organization of the problem occurs, generating alternative strategies, implementation of attempted solutions, and verification of the selected solution. Various methods of studying problem solving exist within the field of psychology including introspection, behavior analysis and behaviorism, simulation, computer modeling, and experimentation.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them (table below). For example, a well-known strategy is trial and error. The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

   Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Further problem solving strategies have been identified (listed below) that incorporate flexible and creative thinking in order to reach solutions efficiently.

Additional Problem Solving Strategies :

• Abstraction – refers to solving the problem within a model of the situation before applying it to reality.
• Analogy – is using a solution that solves a similar problem.
• Brainstorming – refers to collecting an analyzing a large amount of solutions, especially within a group of people, to combine the solutions and developing them until an optimal solution is reached.
• Divide and conquer – breaking down large complex problems into smaller more manageable problems.
• Hypothesis testing – method used in experimentation where an assumption about what would happen in response to manipulating an independent variable is made, and analysis of the affects of the manipulation are made and compared to the original hypothesis.
• Lateral thinking – approaching problems indirectly and creatively by viewing the problem in a new and unusual light.
• Means-ends analysis – choosing and analyzing an action at a series of smaller steps to move closer to the goal.
• Method of focal objects – putting seemingly non-matching characteristics of different procedures together to make something new that will get you closer to the goal.
• Morphological analysis – analyzing the outputs of and interactions of many pieces that together make up a whole system.
• Proof – trying to prove that a problem cannot be solved. Where the proof fails becomes the starting point or solving the problem.
• Reduction – adapting the problem to be as similar problems where a solution exists.
• Research – using existing knowledge or solutions to similar problems to solve the problem.
• Root cause analysis – trying to identify the cause of the problem.

The strategies listed above outline a short summary of methods we use in working toward solutions and also demonstrate how the mind works when being faced with barriers preventing goals to be reached.

One example of means-end analysis can be found by using the Tower of Hanoi paradigm . This paradigm can be modeled as a word problems as demonstrated by the Missionary-Cannibal Problem :

Missionary-Cannibal Problem

Three missionaries and three cannibals are on one side of a river and need to cross to the other side. The only means of crossing is a boat, and the boat can only hold two people at a time. Your goal is to devise a set of moves that will transport all six of the people across the river, being in mind the following constraint: The number of cannibals can never exceed the number of missionaries in any location. Remember that someone will have to also row that boat back across each time.

Hint : At one point in your solution, you will have to send more people back to the original side than you just sent to the destination.

The actual Tower of Hanoi problem consists of three rods sitting vertically on a base with a number of disks of different sizes that can slide onto any rod. The puzzle starts with the disks in a neat stack in ascending order of size on one rod, the smallest at the top making a conical shape. The objective of the puzzle is to move the entire stack to another rod obeying the following rules:

• 1. Only one disk can be moved at a time.
• 2. Each move consists of taking the upper disk from one of the stacks and placing it on top of another stack or on an empty rod.
• 3. No disc may be placed on top of a smaller disk.

  Figure 7.02. Steps for solving the Tower of Hanoi in the minimum number of moves when there are 3 disks.

Figure 7.03. Graphical representation of nodes (circles) and moves (lines) of Tower of Hanoi.

The Tower of Hanoi is a frequently used psychological technique to study problem solving and procedure analysis. A variation of the Tower of Hanoi known as the Tower of London has been developed which has been an important tool in the neuropsychological diagnosis of executive function disorders and their treatment.

GESTALT PSYCHOLOGY AND PROBLEM SOLVING

As you may recall from the sensation and perception chapter, Gestalt psychology describes whole patterns, forms and configurations of perception and cognition such as closure, good continuation, and figure-ground. In addition to patterns of perception, Wolfgang Kohler, a German Gestalt psychologist traveled to the Spanish island of Tenerife in order to study animals behavior and problem solving in the anthropoid ape.

As an interesting side note to Kohler’s studies of chimp problem solving, Dr. Ronald Ley, professor of psychology at State University of New York provides evidence in his book A Whisper of Espionage  (1990) suggesting that while collecting data for what would later be his book  The Mentality of Apes (1925) on Tenerife in the Canary Islands between 1914 and 1920, Kohler was additionally an active spy for the German government alerting Germany to ships that were sailing around the Canary Islands. Ley suggests his investigations in England, Germany and elsewhere in Europe confirm that Kohler had served in the German military by building, maintaining and operating a concealed radio that contributed to Germany’s war effort acting as a strategic outpost in the Canary Islands that could monitor naval military activity approaching the north African coast.

While trapped on the island over the course of World War 1, Kohler applied Gestalt principles to animal perception in order to understand how they solve problems. He recognized that the apes on the islands also perceive relations between stimuli and the environment in Gestalt patterns and understand these patterns as wholes as opposed to pieces that make up a whole. Kohler based his theories of animal intelligence on the ability to understand relations between stimuli, and spent much of his time while trapped on the island investigation what he described as  insight , the sudden perception of useful or proper relations. In order to study insight in animals, Kohler would present problems to chimpanzee’s by hanging some banana’s or some kind of food so it was suspended higher than the apes could reach. Within the room, Kohler would arrange a variety of boxes, sticks or other tools the chimpanzees could use by combining in patterns or organizing in a way that would allow them to obtain the food (Kohler & Winter, 1925).

While viewing the chimpanzee’s, Kohler noticed one chimp that was more efficient at solving problems than some of the others. The chimp, named Sultan, was able to use long poles to reach through bars and organize objects in specific patterns to obtain food or other desirables that were originally out of reach. In order to study insight within these chimps, Kohler would remove objects from the room to systematically make the food more difficult to obtain. As the story goes, after removing many of the objects Sultan was used to using to obtain the food, he sat down ad sulked for a while, and then suddenly got up going over to two poles lying on the ground. Without hesitation Sultan put one pole inside the end of the other creating a longer pole that he could use to obtain the food demonstrating an ideal example of what Kohler described as insight. In another situation, Sultan discovered how to stand on a box to reach a banana that was suspended from the rafters illustrating Sultan’s perception of relations and the importance of insight in problem solving.

Grande (another chimp in the group studied by Kohler) builds a three-box structure to reach the bananas, while Sultan watches from the ground.  Insight , sometimes referred to as an “Ah-ha” experience, was the term Kohler used for the sudden perception of useful relations among objects during problem solving (Kohler, 1927; Radvansky & Ashcraft, 2013).

Solving puzzles.

   Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below (see figure) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

How long did it take you to solve this sudoku puzzle? (You can see the answer at the end of this section.)

   Here is another popular type of puzzle (figure below) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Did you figure it out? (The answer is at the end of this section.) Once you understand how to crack this puzzle, you won’t forget.

   Take a look at the “Puzzling Scales” logic puzzle below (figure below). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

What steps did you take to solve this puzzle? You can read the solution at the end of this section.

Pitfalls to problem solving.

   Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Albert Einstein once said, “Insanity is doing the same thing over and over again and expecting a different result.” Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but she just needs to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

   Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An anchoring bias occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The confirmation bias is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in the table below.

Were you able to determine how many marbles are needed to balance the scales in the figure below? You need nine. Were you able to solve the problems in the figures above? Here are the answers.

   Many different strategies exist for solving problems. Typical strategies include trial and error, applying algorithms, and using heuristics. To solve a large, complicated problem, it often helps to break the problem into smaller steps that can be accomplished individually, leading to an overall solution. Roadblocks to problem solving include a mental set, functional fixedness, and various biases that can cloud decision making skills.

References:

Openstax Psychology text by Kathryn Dumper, William Jenkins, Arlene Lacombe, Marilyn Lovett and Marion Perlmutter licensed under CC BY v4.0. https://openstax.org/details/books/psychology

Review Questions:

1. A specific formula for solving a problem is called ________.

a. an algorithm

b. a heuristic

c. a mental set

d. trial and error

2. Solving the Tower of Hanoi problem tends to utilize a  ________ strategy of problem solving.

a. divide and conquer

b. means-end analysis

d. experiment

3. A mental shortcut in the form of a general problem-solving framework is called ________.

4. Which type of bias involves becoming fixated on a single trait of a problem?

a. anchoring bias

b. confirmation bias

c. representative bias

d. availability bias

5. Which type of bias involves relying on a false stereotype to make a decision?

6. Wolfgang Kohler analyzed behavior of chimpanzees by applying Gestalt principles to describe ________.

a. social adjustment

b. student load payment options

c. emotional learning

d. insight learning

7. ________ is a type of mental set where you cannot perceive an object being used for something other than what it was designed for.

a. functional fixedness

c. working memory

Critical Thinking Questions:

1. What is functional fixedness and how can overcoming it help you solve problems?

2. How does an algorithm save you time and energy when solving a problem?

Personal Application Question:

1. Which type of bias do you recognize in your own decision making processes? How has this bias affected how you’ve made decisions in the past and how can you use your awareness of it to improve your decisions making skills in the future?

anchoring bias

availability heuristic

confirmation bias

functional fixedness

hindsight bias

problem-solving strategy

representative bias

trial and error

working backwards

Answers to Exercises

algorithm:  problem-solving strategy characterized by a specific set of instructions

anchoring bias:  faulty heuristic in which you fixate on a single aspect of a problem to find a solution

availability heuristic:  faulty heuristic in which you make a decision based on information readily available to you

confirmation bias:  faulty heuristic in which you focus on information that confirms your beliefs

functional fixedness:  inability to see an object as useful for any other use other than the one for which it was intended

heuristic:  mental shortcut that saves time when solving a problem

hindsight bias:  belief that the event just experienced was predictable, even though it really wasn’t

mental set:  continually using an old solution to a problem without results

problem-solving strategy:  method for solving problems

representative bias:  faulty heuristic in which you stereotype someone or something without a valid basis for your judgment

trial and error:  problem-solving strategy in which multiple solutions are attempted until the correct one is found

working backwards:  heuristic in which you begin to solve a problem by focusing on the end result

Share This Book

• Increase Font Size

How it works

For Business

Join Mind Tools

Article • 7 min read

Heuristic Methods

Going back to basics.

By the Mind Tools Content Team

You've likely had computer problems in the past. We all have. But did you call up the IT department in a panic? Or did you use the tried-and-tested method of "turning it off and on again"?

This simple step is often all it takes to solve the problem. And it's much quicker and cheaper than sending a technician out to look at your computer every time you encounter a problem.

This is a prime example of a heuristic method at work. It's a simple, standard rule that we refer to when we're problem solving .

What Are Heuristic Methods?

Heuristics are most commonly referred to as "rules of thumb," a term thought to have been coined by Scottish preacher James Durham in his book, "Heaven Upon Earth," published in 1685. In it, Durham refers to "foolish builders, who build by guess, and by rule of thumb." [1]

This method of measurement has its origins in carpenters' ages-old habit of using the tip of their thumb to estimate an inch. (In fact, in Dutch (along with several other European languages), the word for thumb – "duim" – also means inch.)

Heuristic methods are reliable and convenient mental shortcuts that you can use to narrow down your options when you're faced with several different choices, to ease your cognitive load , or to solve problems.

Perhaps you're a hiring manager, and you decide to dismiss any résumés that contain spelling mistakes. Or maybe you're an office manager and you have to make an educated guess about the amount of stationery you need to order every month. In both instances, you are using an heuristic method to meet your objective.

However, it's also important to realize the limitations of heuristic methods. They are best used when the consequences of getting what you're doing wrong is relatively low. Certainly, you might use a heuristic method to help you to sift through a big pile of résumés, but when you make your final decision about who to recruit , greater deliberation and judgment will be needed.

Formalizing a Heuristic Method

Heuristic methods need to be formalized to be most useful to your organization as a whole. This raises them above the level of "gut instinct," and means that you can share them with your colleagues.

Whenever you find yourself calling on your experience to make a judgment, try to work out the rule of thumb that you used to find the solution. Find out what heuristics methods your team members employ as part of your use of explorative techniques such as Management By Walking Around and DILO (Day In the Life Of) . Identify whether any of the methods that you discover could be applied elsewhere within your organization, and if they should even be incorporated into its formal procedures and guidelines.

Heuristic methods can also play an important role in your problem-solving processes. The straw man technique, for example, is similar in approach to heuristics, and it is designed to help you to build on or refine a basic idea. Another approach is to adapt the solution to a different problem to fix yours. TRIZ is a powerful methodology for adopting just such an approach, and is a great source of reliable, experience-based problem-solving approaches.

Heuristics Checklists

It can be helpful to incorporate the heuristic methods that you have discovered into a checklist for newer employees. This way, they can learn from the tried-and-tested knowledge that has been accumulated by their more experienced colleagues.

Such checklists can also be used to refine your decision-making process. For example, in the food industry, the following heuristic checklist might help the product development team to decide whether it's worth test marketing a new pie:

• Does the pie look appetizing in its packaging?
• Can it be packaged so that it won't be damaged in transit?
• Can it be cooked in under 20 minutes, so that busy people will buy it?
• Does it have a shelf life of at least five days from manufacture to expiration date?

This type of list is based on previous product development processes, and on market research. Of course, there's no guarantee that a pie that meets all of these criteria will be successful. But the checklist can help the development team to make a quick "go/no-go" decision , before moving on to the next stage of product development.

The Disadvantages of Using Heuristics

Heuristics are best used when the benefits of making a quick decision outweigh the potential risk of oversimplifying the problem. Remember that heuristics are not about precision, but about having a rough idea of the problem. When you need a more precise answer, you'll need to use a more comprehensive tool. See our problem solving and decision making sections for more than 80 of these, which all focus on different situations.

Heuristic methods are also a great starting point when you or your team are brainstorming but, again, you'll likely need to follow a more detailed and formal procedure when you come to refine your ideas.

The temptation to use mental shortcuts to solve problems and make decisions can be great, particularly if we are under a lot of pressure or have heavy workloads. But cutting corners consistently can lead us to miss important solutions, mishandle problem resolution, and can make us prone to cognitive bias . (The TDODAR decision-making process can help you make good decisions in these situations.)

Instead of rushing to a conclusion that is based on an easy mental shortcut, assess whether the problem is high or low risk. If it is high risk, a more rigorous, knowledge-based approach will likely be needed.

Heuristics, or "rules of thumb," are problem-solving methods that are based on practical experience and knowledge. They allow you to use a "quick fix" to solve a minor problem or to narrow down options. They're also a great starting point for brainstorming or exploring new ideas.

However, remember to be aware of the limitations of heuristic methods. They shouldn't be applied in situations where inaccuracy carries a high degree of risk, or where the consequences of getting things wrong are significant.

[1] Durham, J. (1685). 'Heaven Upon Earth,' Edinburgh: Thomas Lumisden & John Robertson. Sermon ii, p235.

You've accessed 1 of your 2 free resources.

Get unlimited access

Discover more content

Expert Interviews

Authentic Negotiating

Corey Kupfer

How to Guides

Managing Your Emotions

Three Common Emotions and How to Deal With Them Effectively

Add comment

Comments (0)

Be the first to comment!

Team Management

Learn the key aspects of managing a team, from building and developing your team, to working with different types of teams, and troubleshooting common problems.

Sign-up to our newsletter

Subscribing to the Mind Tools newsletter will keep you up-to-date with our latest updates and newest resources.

Subscribe now

Business Skills

Personal Development

Leadership and Management

Member Extras

Most Popular

Newest Releases

SWOT Analysis

How to Build a Strong Culture in a Distributed Team

Mind Tools Store

About Mind Tools Content

Discover something new today

Top tips for delegating.

Delegate work to your team members effectively with these top tips

Ten Dos and Don'ts of Change Conversations

Tips for tackling discussions about change

How Emotionally Intelligent Are You?

Boosting Your People Skills

Self-Assessment

What's Your Leadership Style?

Learn About the Strengths and Weaknesses of the Way You Like to Lead

Recommended for you

How to optimize your energy levels.

Match Your Workload to Your Energy

Business Operations and Process Management

Strategy Tools

Customer Service

Business Ethics and Values

Handling Information and Data

Project Management

Knowledge Management

Self-Development and Goal Setting

Time Management

Presentation Skills

Learning Skills

Career Skills

Communication Skills

Negotiation, Persuasion and Influence

Working With Others

Difficult Conversations

Creativity Tools

Self-Management

Work-Life Balance

Stress Management and Wellbeing

Coaching and Mentoring

Change Management

Managing Conflict

Delegation and Empowerment

Performance Management

Leadership Skills

Developing Your Team

Talent Management

Problem Solving

Decision Making

Member Podcast

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

8.2 Problem-Solving: Heuristics and Algorithms

Learning objectives.

• Describe the differences between heuristics and algorithms in information processing.

When faced with a problem to solve, should you go with intuition or with more measured, logical reasoning? Obviously, we use both of these approaches. Some of the decisions we make are rapid, emotional, and automatic. Daniel Kahneman (2011) calls this “fast” thinking. By definition, fast thinking saves time. For example, you may quickly decide to buy something because it is on sale; your fast brain has perceived a bargain, and you go for it quickly. On the other hand, “slow” thinking requires more effort; applying this in the same scenario might cause us not to buy the item because we have reasoned that we don’t really need it, that it is still too expensive, and so on. Using slow and fast thinking does not guarantee good decision-making if they are employed at the wrong time. Sometimes it is not clear which is called for, because many decisions have a level of uncertainty built into them. In this section, we will explore some of the applications of these tendencies to think fast or slow.

We will look further into our thought processes, more specifically, into some of the problem-solving strategies that we use. Heuristics are information-processing strategies that are useful in many cases but may lead to errors when misapplied. A heuristic is a principle with broad application, essentially an educated guess about something. We use heuristics all the time, for example, when deciding what groceries to buy from the supermarket, when looking for a library book, when choosing the best route to drive through town to avoid traffic congestion, and so on. Heuristics can be thought of as aids to decision making; they allow us to reach a solution without a lot of cognitive effort or time.

The benefit of heuristics in helping us reach decisions fairly easily is also the potential downfall: the solution provided by the use of heuristics is not necessarily the best one. Let’s consider some of the most frequently applied, and misapplied, heuristics in the table below.

In many cases, we base our judgments on information that seems to represent, or match, what we expect will happen, while ignoring other potentially more relevant statistical information. When we do so, we are using the representativeness heuristic . Consider, for instance, the data presented in the table below. Let’s say that you went to a hospital, and you checked the records of the babies that were born on that given day. Which pattern of births do you think you are most likely to find?

Most people think that list B is more likely, probably because list B looks more random, and matches — or is “representative of” — our ideas about randomness, but statisticians know that any pattern of four girls and four boys is mathematically equally likely. Whether a boy or girl is born first has no bearing on what sex will be born second; these are independent events, each with a 50:50 chance of being a boy or a girl. The problem is that we have a schema of what randomness should be like, which does not always match what is mathematically the case. Similarly, people who see a flipped coin come up “heads” five times in a row will frequently predict, and perhaps even wager money, that “tails” will be next. This behaviour is known as the gambler’s fallacy . Mathematically, the gambler’s fallacy is an error: the likelihood of any single coin flip being “tails” is always 50%, regardless of how many times it has come up “heads” in the past.

The representativeness heuristic may explain why we judge people on the basis of appearance. Suppose you meet your new next-door neighbour, who drives a loud motorcycle, has many tattoos, wears leather, and has long hair. Later, you try to guess their occupation. What comes to mind most readily? Are they a teacher? Insurance salesman? IT specialist? Librarian? Drug dealer? The representativeness heuristic will lead you to compare your neighbour to the prototypes you have for these occupations and choose the one that they seem to represent the best. Thus, your judgment is affected by how much your neibour seems to resemble each of these groups. Sometimes these judgments are accurate, but they often fail because they do not account for base rates , which is the actual frequency with which these groups exist. In this case, the group with the lowest base rate is probably drug dealer.

Our judgments can also be influenced by how easy it is to retrieve a memory. The tendency to make judgments of the frequency or likelihood that an event occurs on the basis of the ease with which it can be retrieved from memory is known as the availability heuristic (MacLeod & Campbell, 1992; Tversky & Kahneman, 1973). Imagine, for instance, that I asked you to indicate whether there are more words in the English language that begin with the letter “R” or that have the letter “R” as the third letter. You would probably answer this question by trying to think of words that have each of the characteristics, thinking of all the words you know that begin with “R” and all that have “R” in the third position. Because it is much easier to retrieve words by their first letter than by their third, we may incorrectly guess that there are more words that begin with “R,” even though there are in fact more words that have “R” as the third letter.

The availability heuristic may explain why we tend to overestimate the likelihood of crimes or disasters; those that are reported widely in the news are more readily imaginable, and therefore, we tend to overestimate how often they occur. Things that we find easy to imagine, or to remember from watching the news, are estimated to occur frequently. Anything that gets a lot of news coverage is easy to imagine. Availability bias does not just affect our thinking. It can change behaviour. For example, homicides are usually widely reported in the news, leading people to make inaccurate assumptions about the frequency of murder. In Canada, the murder rate has dropped steadily since the 1970s (Statistics Canada, 2018), but this information tends not to be reported, leading people to overestimate the probability of being affected by violent crime. In another example, doctors who recently treated patients suffering from a particular condition were more likely to diagnose the condition in subsequent patients because they overestimated the prevalence of the condition (Poses & Anthony, 1991).

The anchoring and adjustment heuristic is another example of how fast thinking can lead to a decision that might not be optimal. Anchoring and adjustment is easily seen when we are faced with buying something that does not have a fixed price. For example, if you are interested in a used car, and the asking price is $10,000, what price do you think you might offer? Using $10,000 as an anchor, you are likely to adjust your offer from there, and perhaps offer $9000 or $9500. Never mind that $10,000 may not be a reasonable anchoring price. Anchoring and adjustment does not just happen when we’re buying something. It can also be used in any situation that calls for judgment under uncertainty, such as sentencing decisions in criminal cases (Bennett, 2014), and it applies to groups as well as individuals (Rutledge, 1993).

In contrast to heuristics, which can be thought of as problem-solving strategies based on educated guesses, algorithms are problem-solving strategies that use rules. Algorithms are generally a logical set of steps that, if applied correctly, should be accurate. For example, you could make a cake using heuristics — relying on your previous baking experience and guessing at the number and amount of ingredients, baking time, and so on — or using an algorithm. The latter would require a recipe which would provide step-by-step instructions; the recipe is the algorithm. Unless you are an extremely accomplished baker, the algorithm should provide you with a better cake than using heuristics would. While heuristics offer a solution that might be correct, a correctly applied algorithm is guaranteed to provide a correct solution. Of course, not all problems can be solved by algorithms.

As with heuristics, the use of algorithmic processing interacts with behaviour and emotion. Understanding what strategy might provide the best solution requires knowledge and experience. As we will see in the next section, we are prone to a number of cognitive biases that persist despite knowledge and experience.

Key Takeaways

• We use a variety of shortcuts in our information processing, such as the representativeness, availability, and anchoring and adjustment heuristics. These help us to make fast judgments but may lead to errors.
• Algorithms are problem-solving strategies that are based on rules rather than guesses. Algorithms, if applied correctly, are far less likely to result in errors or incorrect solutions than heuristics. Algorithms are based on logic.

Bennett, M. W. (2014). Confronting cognitive ‘anchoring effect’ and ‘blind spot’ biases in federal sentencing: A modest solution for reforming and fundamental flaw. Journal of Criminal Law and Criminology , 104 (3), 489-534.

Kahneman, D. (2011). Thinking, fast and slow. New York, NY: Farrar, Straus and Giroux.

MacLeod, C., & Campbell, L. (1992). Memory accessibility and probability judgments: An experimental evaluation of the availability heuristic.  Journal of Personality and Social Psychology, 63 (6), 890–902.

Poses, R. M., & Anthony, M. (1991). Availability, wishful thinking, and physicians’ diagnostic judgments for patients with suspected bacteremia.  Medical Decision Making,  11 , 159-68.

Rutledge, R. W. (1993). The effects of group decisions and group-shifts on use of the anchoring and adjustment heuristic. Social Behavior and Personality, 21 (3), 215-226.

Statistics Canada. (2018). Ho micide in Canada, 2017 . Retrieved from https://www150.statcan.gc.ca/n1/en/daily-quotidien/181121/dq181121a-eng.pdf

Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability.  Cognitive Psychology, 5 , 207–232.

Psychology - 1st Canadian Edition Copyright © 2020 by Sally Walters is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

Heuristics For Problem Solvers

Adapted from Meiring, S. P. (1980). Problem solving – A basic mathematics goal . Columbus: Ohio Department of Education.

A heuristic is a thinking strategy, something that can be used to tease out further information about a problem and that can thus help you figure out what to do when you don't know what to do. Here are twenty heuristics that can be useful when you are facing what seems intractable. They help you to monitor your thought processes: to step back and watch yourself at work, thus keeping your cool.

• Ask somebody else how to do it. This is probably the most-used strategy, world-wide, though it's not one we encourage our students to use, at least not initially. (Google it goes here too, and is never encouraged.)
• Guess and try (guess, check, and revise). Your guess might be right! But incorrect guesses can often suggest a direction toward a solution. (N.B. a spreadsheet is a powerful aid in guessing and trying: set up the relationships and plug in a number to see if you get what you want. If you don't, it's easy to try another one. And another. And another...)
• Restate the problem using words that make sense to you. One way to do this is to explain the problem to someone else. Often this is all it takes for the light to dawn.
• Organize information into a table or chart. Having it laid out clearly in front of you frees your mind up for thinking, and perhaps you can use the organized data to generate more information.
• Draw a picture of problem information. Translate problem information into pictures, diagrams, sketches, glyphs, arrows, or...?
• Make a model of the problem. The model might be a physical or mental model, perhaps using a computer. You might vary the problem information to see how or whether it changes the model.
• Look for patterns – any kind of patterns: number patterns, verbal patterns, spatial/visual patterns, patterns in time, patterns in sound. (Some people define mathematics as the science of patterns.)
• Act the problem out, if it's stated in a narrative form. This can have the same effect as drawing a picture. What's more, doing the problem might disclose incorrect assumptions you are making.
• Invent notation. Name things in the problem (known or unknown) using words or symbols, including relationships between problem components.
• Write equations. An equation is simply the same thing named two different ways.
• Check all possibilities in a systematic way. A table or chart may help you to be systematic.
• Work backwards from the end condition to the beginning condition. This is particularly helpful when letting a variable (letter) represent an unknown.
• Identify subgoals in the problem. Break up the problem into a sequence of smaller problems ("if I knew this, then I could get that").
• Make the problem simpler. Use easier or smaller numbers; or look at extreme cases (for example, assuming that the maximum amount of one of the varying quantities is used). Often you can use what you learn from the mini-version to help unlock the big one.
• Restate the problem yet again. After working on the problem for a time, back off a bit and put it into your own words in still a different way, since now you know more about it.
• Change your point of view. Use your imagination to change the way you are looking at the problem – turn it upside down, or pull it inside out.
• Check for hidden assumptions that you may be making (you may be making the problem harder than it really is). These assumptions are often found by changing the given numbers or conditions and looking to see what happens.
• Identify needed and given information clearly. You may not need to find everything you think you need to find, for instance.
• Make up your own technique. It is your mind, after all; use mental actions that make sense to you. The key is to do something that engages you with the problem.
• Try combinations of these heuristics.

The above heuristics are those which are easily pointed out to students as they engage with problems in the classroom. However, real world problems are often those which are confronted many times over or on increasingly complex levels. For those, George Polya, the father of modern problem solving heuristics, identified a fifth class (E) called looking back heuristics. We include those here for completeness, but also with the teaching caveat that solutions often improve and insights grow deeper after the initial "pressure" to produce a solution has been resolved. Subsequent looks at a problem situation are invariably deeper and can lead to wonderful surprises.

• Check your solution. Substitute your answer or results back into the problem. Are all of the conditions satisfied?
• Find another solution. There may be more than one answer. Make sure you have them all.
• Solve the problem a different way. Your first solution will seldom be the best solution. Now that the pressure is off, you may readily find other ways to solve the problem.
• Solve a related problem. Steve Brown and Marion Walter in their book, The Art of Problem Posing , suggest the "What if not?" technique. What if the train goes at a different speed? What if there are 8 children, instead of 9? What if...? Fascinating discoveries can be made in this way, leading to:
• Generalize the solution. Can you glean from your solution how it can be made to fit a whole class of related situations? Can you prove your result?

7.3 Problem Solving

Learning objectives.

By the end of this section, you will be able to:

• Describe problem solving strategies
• Define algorithm and heuristic
• Explain some common roadblocks to effective problem solving and decision making

People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

Problem-Solving Strategies

When you are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them ( Table 7.2 ). For example, a well-known strategy is trial and error . The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Everyday Connection

Solving puzzles.

Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below ( Figure 7.7 ) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

Here is another popular type of puzzle ( Figure 7.8 ) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Take a look at the “Puzzling Scales” logic puzzle below ( Figure 7.9 ). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

Pitfalls to Problem Solving

Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but they just need to go to another doorway, instead of trying to get out through the locked doorway. A mental set is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. Duncker (1945) conducted foundational research on functional fixedness. He created an experiment in which participants were given a candle, a book of matches, and a box of thumbtacks. They were instructed to use those items to attach the candle to the wall so that it did not drip wax onto the table below. Participants had to use functional fixedness to overcome the problem ( Figure 7.10 ). During the Apollo 13 mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

Link to Learning

Check out this Apollo 13 scene about NASA engineers overcoming functional fixedness to learn more.

Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An anchoring bias occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The confirmation bias is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the availability heuristic is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision . Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in Table 7.3 .

Watch this teacher-made music video about cognitive biases to learn more.

Were you able to determine how many marbles are needed to balance the scales in Figure 7.9 ? You need nine. Were you able to solve the problems in Figure 7.7 and Figure 7.8 ? Here are the answers ( Figure 7.11 ).

As an Amazon Associate we earn from qualifying purchases.

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Access for free at https://openstax.org/books/psychology-2e/pages/1-introduction

• Authors: Rose M. Spielman, William J. Jenkins, Marilyn D. Lovett
• Publisher/website: OpenStax
• Book title: Psychology 2e
• Publication date: Apr 22, 2020
• Location: Houston, Texas
• Book URL: https://openstax.org/books/psychology-2e/pages/1-introduction
• Section URL: https://openstax.org/books/psychology-2e/pages/7-3-problem-solving

© Jan 6, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

• Memberships

Heuristic Method

Heuristic Method: this article explains the concept of the Heuristic Method , developed by George Pólya in a practical way. After reading it, you will understand the basics of this powerful Problem Solving tool.

What is the Heuristic Method?

A heuristic method is an approach to finding a solution to a problem that originates from the ancient Greek word ‘eurisko’, meaning to ‘find’, ‘search’ or ‘discover’. It is about using a practical method that doesn’t necessarily need to be perfect. Heuristic methods speed up the process of reaching a satisfactory solution.

Previous experiences with comparable problems are used that can concern problem situations for people, machines or abstract issues. One of the founders of heuristics is the Hungarian mathematician György (George) Pólya , who published a book about the subject in 1945 called ‘How to Solve It’. He used four principles that form the basis for problem solving.

Heuristic method: Four principles

Pólya describes the following four principles in his book:

• try to understand the problem
• make a plan
• carry out this plan
• evaluate and adapt

If this sequence doesn’t lead to the right solution, Pólya advises to first look for a simpler problem.

A solution may potentially be found by first looking at a similar problem that was possible to solve. With this experience, it’s possible to look at the current problem in another way.

First principle of the heuristic method: understand the problem

It’s more difficult than it seems, because it seems obvious. In truth, people are hindered when it comes to finding an initially suitable approach to the problem.

It can help to draw the problem and to look at it from another angle. What is the problem, what is happening, can the problem be explained in other words, is there enough information available, etc. Such questions can help with the first evaluation of a problem issue.

Second principle of the heuristic method: make a plan

There are many ways to solve problems. This section is about choosing the right strategy that best fits the problem at hand. The reversed ‘working backwards’ can help with this; people assume to have a solution and use this as a starting point to work towards the problem.

It can also be useful to make an overview of the possibilities, delete some of them immediately, work with comparisons, or to apply symmetry. Creativity comes into play here and will improve the ability to judge.

Third principle of the heuristic method: carry out the plan

Once a strategy has been chosen, the plan can quickly be implemented. However, it is important to pay attention to time and be patient, because the solution will not simply appear.

If the plan doesn’t go anywhere, the advice is to throw it overboard and find a new way.

Fourth principle of the heuristic method: evaluate and adapt

Take the time to carefully consider and reflect upon the work that’s already been done. The things that are going well should be maintained, those leading to a lesser solution, should be adjusted. Some things simply work, while others simply don’t.

There are many different heuristic methods, which Pólya also used. The most well-known heuristics are found below:

1. Dividing technique

The original problem is divided into smaller sub-problems that can be solved more easily. These sub-problems can be linked to each other and combined, which will eventually lead to the solving of the original problem.

2. Inductive method

This involves a problem that has already been solved, but is smaller than the original problem. Generalisation can be derived from the previously solved problem, which can help in solving the bigger, original problem.

3. Reduction method

Because problems are often larger than assumed and deal with different causes and factors, this method sets limits for the problem in advance. This reduces the leeway of the original problem, making it easier to solve.

4. Constructive method

This is about working on the problem step by step. The smallest solution is seen as a victory and from that point consecutive steps are taken. This way, the best choices keep being made, which will eventually lead to a successful end result.

5. Local search method

This is about the search for the most attainable solution to the problem. This solution is improved along the way. This method ends when improvement is no longer possible.

Exact solutions versus the heuristic method

The heuristic approach is a mathmatical method with which proof of a good solution to a problem is delivered. There is a large number of different problems that could use good solutions. When the processing speed is equally as important as the obtained solution, we speak of a heuristic method.

The Heuristic Method only tries to find a good, but not necessarily optimal, solution. This is what differentiates heuristics from exact solution methods, which are about finding the optimal solution to a problem. However, that’s very time consuming, which is why a heuristic method may prove preferable. This is much quicker and more flexible than an exact method, but does have to satisfy a number of criteria.

It’s Your Turn

What do you think? Is the Heuristic Method applicable in your personal or professional environment? Do you recognize the practical explanation or do you have more suggestions? What are your success factors for solving problems

Share your experience and knowledge in the comments box below.

More information

• Groner, R., Groner, M., & Bischof, W. F. (2014). Methods of heuristics . Routledge .
• Newell, A. (1983). The heuristic of George Polya and its relation to artificial intelligence . Methods of heuristics, 195-243.
• Polya, G. (2014, 1945). How to solve it: A new aspect of mathematical method . Princeton university press .

How to cite this article: Mulder, P. (2018). Heuristic Method . Retrieved [insert date] from ToolsHero: https://www.toolshero.com/problem-solving/heuristic-method/

Add a link to this page on your website: <a href=”https://www.toolshero.com/problem-solving/heuristic-method/”>ToolsHero: Heuristic Method</a>

Published on: 29/05/2018 | Last update: 04/03/2022

Did you find this article interesting?

Your rating is more than welcome or share this article via Social media!

Average rating 4.6 / 5. Vote count: 13

No votes so far! Be the first to rate this post.

We are sorry that this post was not useful for you!

Let us improve this post!

Tell us how we can improve this post?

Patty Mulder

Patty Mulder is an Dutch expert on Management Skills, Personal Effectiveness and Business Communication. She is also a Content writer, Business Coach and Company Trainer and lives in the Netherlands (Europe). Note: all her articles are written in Dutch and we translated her articles to English!

ALSO INTERESTING

Crowdsourcing: the meaning, definition and some examples

Systematic Inventive Thinking (SIT)

CATWOE Analysis: theory and example

Leave a reply cancel reply.

You must be logged in to post a comment.

BOOST YOUR SKILLS

Toolshero supports people worldwide ( 10+ million visitors from 100+ countries ) to empower themselves through an easily accessible and high-quality learning platform for personal and professional development.

By making access to scientific knowledge simple and affordable, self-development becomes attainable for everyone, including you! Join our learning platform and boost your skills with Toolshero.

POPULAR TOPICS

• Change Management
• Marketing Theories
• Problem Solving Theories
• Psychology Theories

ABOUT TOOLSHERO

• Free Toolshero e-book
• Memberships & Pricing

Home Blog Business Using Heuristic Problem-Solving Methods for Effective Decision-Making

Using Heuristic Problem-Solving Methods for Effective Decision-Making

Problem-solving capability and effective decision making are two of the most prized capabilities of any leader. However, one cannot expect these traits to be simply present by default in an individual, as both require extensive analysis of the root cause of issues and to know what to look for when anticipating a gain. In a previous article, we brought you  5 Problem-Solving Strategies to Become a Better Problem Solver . This time we have something that can help you dig deep to resolve problems, i.e. using heuristic problem-solving methods for effective decision-making.

What are Heuristics?

Heuristics are essentially problem-solving tools that can be used for solving non-routine and challenging problems. A heuristic method is a practical approach for a short-term goal, such as solving a problem. The approach might not be perfect but can help find a quick solution to help move towards a reasonable way to resolve a problem.

Example: A computer that is to be used for an event to allow presenters to play PowerPoint presentations via a projector malfunctions due to an operating system problem. In such a case a system administrator might quickly refresh the system using a backup to make it functional for the event. Once the event concludes the system administrator can run detailed diagnostic tests to see if there are any further underlying problems that need to be resolved.

In this example, restoring the system using a backup was a short-term solution to solve the immediate problem, i.e. to make the system functional for the event that was to start in a few hours. There are a number of heuristic methods that can lead to such a decision to resolve a problem. These are explained in more detail in the sections below.

Examples of Heuristic Methods Used for Challenging and Non-Routine Problems

Heuristic methods can help ease the cognitive load by making it easy to process decisions. These include various basic methods that aren’t rooted in any theory per se but rather rely on past experiences and common sense. Using heuristics one can, therefore, resolve challenging and non-routine problems. Let’s take a look at some examples.

A Rule of Thumb

This includes using a method based on practical experience. A rule of thumb can be applied to find a short-term solution to a problem to quickly resolve an issue during a situation where one might be pressed for time.

Example: In the case of the operating system failure mentioned earlier, we assume that the PC on which PowerPoint presentations are to be run by presenters during an event is getting stuck on the start screen. Considering that the event is about to start in 2 hours, it is not practical for the system administrator to reinstall the operating system and all associated applications, hotfixes and updates, as it might take several hours. Using a rule of thumb, he might try to use various tried and tested methods, such as trying to use a system restore point to restore the PC without deleting essential files or to use a backup to restore the PC to an earlier environment.

An Educated Guess

An educated guess or guess and check can help resolve a problem by using knowledge and experience. Based on your knowledge of a subject, you can make an educated guess to resolve a problem.

Example: In the example of the malfunctioning PC, the system administrator will have to make an educated guess regarding the best possible way to resolve the problem. The educated guess, in this case, can be to restore the system to a backup instead of using system restore, both of which might take a similar amount of time; however, the former is likely to work better as a quick fix based on past experience and knowledge of the system administrator.

Trial and Error

This is another heuristic method to problem-solving where one might try various things that are expected to work until a solution is achieved.

Example: The system administrator might try various techniques to fix the PC using trial and error. He might start with checking if the system is accessible in safe mode. And if so, does removing a newly installed software or update solve the problem? If he can’t access the system at all, he might proceed with restoring it from a backup. If that too fails, he might need to quickly opt for a wipe and load installation and only install PowerPoint to ensure that at least presenters can run presentations on the PC. In this case he can perform other required software installations after the event.

An Intuitive Judgment

Intuitive judgment does not result from a rational analysis of a situation or based on reasoning. It is more of a feeling one has which may or may not lead to the desired outcome. Sometimes, intuitive judgement can help resolve problems. Perhaps the most rational way to describe an intuition is that it is some type of calculation at the subconscious level, where you can’t put your finger on the reason why you think something might be the way it is.

Example: The system administrator might have a feeling that the PC is not working because the hard drive has failed. This might be an intuitive judgment without hard evidence. He might quickly replace the hard drive to resolve the problem. Later, after he runs diagnostics on the old hard drive, he might realize that it was indeed that hard drive that was faulty and trying to fix it would have been a waste of time. In this case, he might be able to solve a problem using intuitive judgment.

Stereotyping

A stereotype is an opinion which is judgmental rather than rational. Certain types of possessions for example create a stereotype of social status. A person who wears an expensive watch might be deemed rich, although he might simply have received it as a gift from someone, instead of being rich himself.

Example: A certain company might have developed a bad reputation of developing faulty hard drives. If the systems administrator sees the name of that company on the hard drive when opening the faulty PC, he might think that the hard drive is faulty based on stereotyping and decide to replace it.

Profiling is used to systematically analyze data to understand its dynamics. Profiling as a heuristic method for problem-solving might entail analyzing data to understand and resolve a problem or to look for patterns, just like a root cause analysis .

Example: To solve the issue of the faulty PC, a system administrator might look for similar patterns which might have led to the problem. He might search online for solutions via online forums to understand what might have caused the issue. He might also look at the information associated with recently installed software and updates to see if something conflicted with the operating system. During the profiling process, he might realize that software he installed yesterday before shutting down the PC is the cause of the problem, since similar issues have been reported by other users. He might try to remove the software using Safe Mode or by removing its files by running the computer from a bootable disc drive.

Common Sense

Common sense is the use of practical judgment to understand something. The use of common sense is also a heuristic method used for problem-solving.

Example: When dealing with a faulty PC the system administrator sees smoke coming out of the PC. In this case, it is common sense that a hardware component is faulty. He shuts down the PC, removes the power cord and investigates the issue further based on common sense. This is because keeping the system linked to a power socket amidst smoke emitting from the PC can only make things worse. It is common sense to turn off everything and take the necessary precautions to investigate the issue further.

How are Heuristic Methods Used in Decision-Making?

There are a number of formal and informal models of heuristics used for decision making. Let’s take a look at a few of the formal models of heuristics used for decision making.

Formal Models of Heuristics

Fast-and-frugal tree.

A fast-and-frugal tree is a classification or decision tree. It is a graphical form that helps make decisions. For example, a fast-and-frugal tree might help doctors determine if a patient should be sent to a regular ward or for an emergency procedure. fast-and-frugal trees are methods for making decisions based on hierarchical models, where one has to make a decision based on little information.

Fluency Heuristic

In psychology, fluency heuristic implies an object that can be easily processed and deemed to have a higher value, even if it is not logical to assume this. Understanding the application of fluency heuristic can help make better decisions in a variety of fields. Fluency heuristic is more like sunk cost fallacy .

For example, a designer might design a user interface that is easier for users to process, with fewer buttons and easily labeled options. This can help them think fast, work quicker and improve productivity. Similarly, the concept might be used in marketing to sell products using effective marketing techniques. Even if two products are identical, a consumer might pick one over the other based on fluency heuristic. The consumer might deem the product to be better for his needs, even if it is the same as the other one.

Gaze Heuristic

Assume that you aim to catch a ball. Based on your judgment you would leap to catch the ball. If you were to leave yourself to instinct, you will end up at the same spot to catch the ball at a spot you would predict it to fall. This is essentially gaze heuristic. The concept of gaze heuristic is thought to be applied for simple situations and its applications are somewhat limited.

Recognition Heuristic

If there are two objects, one recognizable and the one isn’t, the person is likely to deem the former to be of greater value. A simple example of recognition heuristic is branding. People get used to brand logos, assuming them to be of high quality. This helps brands to sell multiple products using recognition heuristic. So, if you are looking to buy an air conditioner and come across two products, A and B, where A is a brand you know and B is a new company you don’t recognize, you might opt for A. Even if B is of better quality, you might simply trust A because you have been buying electronics from the brand for many years and they have been of good quality.

Satisficing

Satisficing entails looking for alternatives until an acceptable threshold can be ensured. Satisficing in decision making implies selecting an option which meets most needs or the first option which can meet a need, even if it is not the optimal solution. For example, when choosing between early retirement or continuing service for 2 or 3 more years, one might opt for early retirement assuming that it would meet the individual’s needs.

Similarity Heuristic

Similarity heuristic is judgment based on which is deemed similar, if something reminds someone of good or bad days, something similar might be considered the same. Similarity heuristics is often used by brands to remind people of something that they might have sentimental value for.

Someone might buy a limited-edition bottle of perfume that is being sold in a packaging style that was replaced 20 years ago. Assuming that sales were great in those days, the company might sell such limited-edition perfume bottles in the hope of boosting sales. Consumers might buy them simply because they remind them of the ‘good old days’, even though the product inside might not even be of the same but rather similar to what it used to be. Many consumers claim to buy these types of products claiming that it reminds them of a fond memory, such as their youth, marriage or  first job, when they used the product back in the day.

Final Words

Heuristics play a key role in decision making and affect the way we make decisions. Understanding heuristics can not only help resolve problems but also understand biases that affect effective decision making. A business decision or one that affects one’s health, life, or well-being cannot rely merely on a hunch. Understanding heuristics and applying them effectively can therefore help make the best possible decisions. Heuristic methods are not only used in different professions and personal decision making but are also used in artificial intelligence and programming.

Modern anti-virus software for instance uses heuristic methods to dig out the most elusive malware. The same rule can be essentially applied to decision making, by effectively using heuristics to resolve problems and to make decisions based on better judgment.

Like this article? Please share

Common Sense, Decision Making, Educated Guess, Heuristics, Judgment, Problem Solving, Profiling, Rule of Thumb, Stereotyping, Trial and Error Filed under Business

Related Articles

Filed under Business • January 16th, 2024

The OODA Loop Decision-Making Model and How to Use it for Presentations

OODA Loop is a model that supports people and companies when defining important decisions in teams or individuals. See here how to apply it in presentation slide design.

Filed under Business • October 5th, 2023

SCAMPER Technique & Ideation Method (Quick Guide for Interactive Presentations)

SCAMPER is a technique that provides a structured approach towards thinking outside the box. In this article, we explore how this technique can be used.

Filed under Business • October 2nd, 2023

How to Write a Problem Statement: Hands-On Guide With Examples

A well-written problem statement defines the stage for successful solution development and garnering support from stakeholders. Helpful tips here.

Leave a Reply

• Corporate Courses |
• Employee Courses |
• Leadership Courses |
• Limited Time Offer

Exploring Heuristic Methods For Problem Solving

Heuristic methods refer to experience-based techniques for mastering problem solving , learning , and discovery that find solutions that are good enough but may not be optimal.

Heuristics are mental shortcuts that allow people to solve problems and make judgments quickly based on intuitive judgments.

Background In Heuristic Methods In Business

Heuristic methods have long been used in business as a practical approach to making decisions and judgments efficiently.

The rationale behind using heuristics in business is that they allow managers and leaders to make timely assessments and choices without getting bogged down in a lengthy optimization process.

Some key reasons why businesses rely on heuristic methods include:

• Business problems are often complex with many variables, making strict optimization difficult. Heuristics allow for quick solutions.
• There is often uncertainty and ambiguity in business situations. Heuristics help managers make decent decisions with incomplete information.
• Businesses need to be agile and adapt quickly to changing conditions. Heuristics facilitate fast decision making.
• Finding optimal solutions can require significant time, resources, and information that businesses often don’t have. Heuristics provide good enough solutions.

Examples Of Heuristic Methods Used In Business

Here are 7 common heuristic techniques used in a business context:

• Satisficing: Managers set a minimum threshold or standard and choose the first option that meets it rather than finding the optimal solution.
• Rules of Thumb: Businesses use simple decision rules gained from experience, such as setting prices at double the production cost.
• Extrapolation: Projecting historical data into the future based on current trends, such as forecasting sales.
• Estimation: Gauging an approximate value when the precise value is unknown, like estimating project costs.
• Elimination-by-Aspects: Removing options based on a key disqualifying trait rather than systematically comparing all options.
• Recognition: Making decisions by recognizing similarities of a current situation to past experiences.
• Availability : Judging an event’s likelihood based on how readily examples come to mind. Used to assess business risks.

Challenges With Relying On Heuristics

While heuristic methods are very useful in business, overreliance on heuristics can also lead to poor decisions and cognitive biases. Some limitations to keep in mind include:

• Heuristics may lead to suboptimal solutions rather than optimal ones.
• They are prone to biases which can skew judgment.
• Overuse of heuristics can inhibit creative problem solving .
• They rely heavily on the intuition and past experience of the individual.
• Changing environments can make previously useful heuristics less relevant.

Using Heuristics Positively In Business

Despite their shortcomings, heuristics can be leveraged productively in business. Here are 10 tips:

• Clearly define the problem before applying a heuristic.
• Use heuristics as one input but don’t rely entirely on them.
• Combine heuristics with optimization models when possible.
• Leverage heuristics to direct and focus optimization techniques.
• Apply multiple heuristics and look for consensus.
• Update heuristics as the business environment evolves.
• Weigh heuristic solutions against data and metrics when available.
• Recognize the influence of biases and test assumptions.
• Consider when heuristics may lead to suboptimal results or cognitive biases.
• Ensure heuristics align with organizational values and goals.

Heuristic methods provide business leaders with practical mental shortcuts for making timely decisions with limited information.

While overreliance on heuristics can be risky, used judiciously and strategically they offer a valuable decision-making tool.

Businesses should leverage heuristics while being aware of their limitations and mitigating the risks of biases. With the right approach, they can enhance agility and performance.

Understanding The Availability Heuristic: A Mental Shortcut

The Importance Of An Optimal Learning Environment

Improve Your Listening Skills With These Training Techniques

Creating An Effective Training Plan: A Step-By-Step Guide

25 Best Resume Tips That Will Get You A Job

Kaizen: The Path To Continuous Improvement In Business

How To Deal With Manipulative People In The Workplace

There’s always more learning to explore..

Add to cart

Buy Quality Management Skills Workbooks

Buy Corporate Structure Skills Workbooks

Buy Issues In An Organization Workbooks

Buy Corporate Culture Skills Workbooks

Buy Negotiation Skills Workbooks

Buy Marketing Skills Workbooks

Buy Conflict Resolution Skills Workbooks

Buy Leadership Influence Skills Workbooks

Buy Delegation In Leadership Workbooks

Buy Leadership Skills Workbooks

Buy Job Design Skills Workbooks

Buy Job Analysis Skills Workbooks

Trusted by leading commercial and public sector organizations..

All-In-One Course Materials For Enterprises

Say goodbye to the ever-challenging task of developing your own training courses. Our intuitive training course material enables you  to download, share, and deliver your own courses.

Saving You Time.

Give your company a faster, more flexible way of presenting training courses. Access, brand, and present training courses all from one easy-to-use download.

Want To Save More On Your Training Course Materials?

• 50+ fully tested sets of training course materials
• 17+ training guides (PDFs)
• 100% customizable content
• 90% savings on normal prices
• and more...

Frequently Asked Questions.

Oak Innovation simplifies the course creation process. Our readymade training course material will save you time. And, you'll get instant access to the training content needed to meet the needs of your audience.

You don’t need any detailed expertize to present our training course material – simply focus on your course delivery, and we’ll handle the rest. You get instant access to workbooks, guides, and resources.

Our pricing is really simple. Each set of course material costs $80.

1. Select the course you want to deliver. 2. Add the course materials to the shopping cart. 3. Securely pay using all major debit/credit cards. 4. Get instant access via a secure download page. 5. Get an email with download instructions. 6. Unzip your order and access everything in MS Office format.

Yes. You can add your logo and brand the course material as your own.

Yes, you can see a full list of our courses in our  shop .

Our white-label training course materials can be used to teach all categories of employees. Senior Leadership Teams - Leadership teams play a critical role in organizations. These course materials will equip them with the skills needed to transform their companies into the future. Mid-Level Managers, Supervisors And HR Professionals - Our training course materials enable mid-level managers, supervisors and HR professionals to lead and develop their teams for success. Frontline Employees - Core to all organizations, frontline employees will benefit directly from these training course materials. Small Business Owners And Entrepreneurs - Attending courses based on these training course materials will equip all entrepreneurs and their teams with the skills, knowledge and abilities required to revolutionize their companies.

Which Training Course Materials Are Right For You?

Heuristics Unleashed: A Comprehensive Guide to Heuristics in Computer Science and Programming

Heuristics are nothing new, they play an important role in our daily lives, in both problem-solving and data-driven decision-making (DDDM) . As nowadays, the world is full of information, and our brains are only capable of processing a certain amount of it, heuristics help us a lot in this sense. Because if you would try to analyze every single aspect of every situation or decision, you would never get anything done.

We take thousands of decisions every single day and most of them we don’t really think about, we “know” how to behave in certain situations based on our experience and that’s what heuristics are about. When we are trying to solve a problem or make a decision, we often turn to these mental shortcuts when we need a quick solution.

Introduction to Heuristics

In the world of computer science, heuristics play a vital role in tackling complex problems and providing efficient solutions. This introductory section will explore the concept of heuristics and highlight their significance in problem-solving.

Definition of Heuristics

Heuristics is practical problem-solving techniques or methods used to find quick and effective solutions when dealing with complex issues. They are only sometimes guaranteed to produce the best or optimal solution, but they often lead to satisfactory results within a reasonable time frame. Heuristics are particularly useful when dealing with problems that have incomplete, uncertain, or imprecise information or when the search space is too ample for a complete, exhaustive search.

Importance of Heuristics in Problem Solving

The importance of heuristics in problem-solving is evident in their versatility and adaptability across different computer science domains. Some of the reasons why heuristics are crucial for problem-solving include:

• Efficiency : Heuristics can significantly reduce the time and resources needed to solve problems, especially when the search space is enormous, or the problem is too complex.
• Simplicity : Heuristic methods are often easier to implement and understand than complicated algorithms, making them more accessible to a broader audience.
• Flexibility : Heuristics can be applied to various problem domains, often with minor modifications, making them versatile problem-solving tools.
• Robustness : In situations where the available data is incomplete, uncertain, or noisy, heuristics can still provide helpful solutions, making them applicable to real-world problems.

History of Heuristics in Computer Science

Heuristics have been crucial to the growth and advancement of computer science. Here's how the history of heuristics and how they have changed over time.

Early Beginnings

Ancient Greek mathematicians and philosophers used heuristic techniques to solve mathematical and logical issues, giving rise to heuristic usage. 

Yet, with the development of artificial intelligence (AI) research in the 1950s and 1960s, heuristics were formally introduced in computer science for the first time.

Alan Turing, one of the early AI pioneers, first suggested a heuristic search in his landmark article " Computing Machines and Intelligence ." The exploration of heuristics as a tool to solve challenging problems in AI and computer science was made possible thanks to Turing's work.

George Pólya, another important person, wrote the famous book " How to Solve It " in 1945. It offered a collection of heuristics for resolving mathematical issues. Many computer scientists and researchers were motivated by Pólya's efforts to

Evolution of Heuristic Techniques

Over the years, heuristic techniques have evolved and diversified to address various complex problems in computer science. Some of the most notable developments in the history of heuristics include:

• Game Theory : In the 1950s and 1960s, researchers like Claude Shannon and Arthur Samuel developed early heuristics to explore optimal game strategies like chess and checkers. Their work paved the way for more advanced heuristic techniques used in game theory today.
• Optimization : In the 1970s, researchers began developing metaheuristic optimization algorithms, such as genetic and simulated annealing, to find near-optimal solutions to complex optimization problems.
• Machine Learning : The 1980s and 1990s witnessed significant advancements in machine learning techniques, such as decision trees and neural networks, which rely on heuristic methods to learn from data and make predictions.
• Human-Computer Interaction : Heuristic evaluation, a method for identifying usability issues in user interfaces, was introduced by Jakob Nielsen in the 1990s, highlighting the application of heuristics in human-computer interaction.
• As computer science continues to evolve, so do heuristic techniques, with researchers constantly developing new and innovative ways to apply heuristics to tackle increasingly complex problems.

So, What is Heuristic Programming?

Heuristics are mental shortcuts that help us make decisions and judgments quickly without having to spend a lot of time researching and analyzing information. They usually involve focusing on one aspect of a complex problem and ignoring others. They work well under most circumstances, but they can lead to systematic deviations from logic, probability, or rational choice. Examples that employ heuristics include using a rule of thumb, an educated guess, an intuitive judgment, a guesstimate, stereotyping, profiling, or common sense.

Heuristics in Software Development

Heuristics have become indispensable to software engineering , helping developers create more efficient, maintainable, and user-friendly software. This section will explore various ways heuristics are employed in software development.

Design Patterns

Design patterns are reusable solutions to common problems that arise in software design. They are heuristics that software developers can apply when faced with specific design challenges. By leveraging these well-established patterns, developers can create more maintainable and scalable software while avoiding common pitfalls.

Some widely used design patterns include:

• Singleton : Assures a class has just one instance and offers a universal access point to that instance.
• Factory Method : Establishes a framework for instantiating objects in a superclass, allowing subclasses to select the objects they want to use.
• Observer : Establishes a one-to-many relationship between objects so that all of its dependents are automatically informed and updated when one changes.

Agile Development

Agile development methodologies , such as Scrum and Kanban, have become famous for managing software projects more efficiently in recent years. These methodologies incorporate heuristics to streamline development, improve collaboration, and deliver high-quality software.

Some critical heuristics in agile development include:

• Iterative Development : Agile methodologies promote short development cycles, allowing teams to gather feedback continuously, identify issues, and adjust their plans accordingly.
• Time-boxing : Setting strict time limits for tasks helps teams maintain focus and prevents them from getting bogged down in unnecessary details.
• Daily Stand-ups : Regular short meetings enable team members to share updates, identify roadblocks, and ensure everyone is on the same page.
• Prioritization : Agile methodologies prioritize tasks based on their value to the end user, ensuring that the most critical features are delivered first.

Code Smells and Refactoring

Code smells indicate potential problems in the source code, often resulting from poor design choices or programming practices. Heuristics can be used to identify these code smells and guide developers in refactoring their code to improve its maintainability, readability, and overall quality.

Some examples of code smells, and corresponding refactoring techniques include:

• Long Method : A method that is too long and difficult to understand can be broken down into smaller, more manageable processes.
• Duplicate Code : Identical or similar code in multiple locations can be consolidated into a single reusable method or class.
• Feature Envy : When a method accesses data from another class more than its data, moving the technique to that class may be more appropriate.
• Software engineers can produce more effective, maintainable, and user-friendly software that satisfies the requirements of their customers and end users by utilizing heuristics in the development process.

Heuristics in Computer Sciences

In computer science, a heuristic is a problem-solving strategy or method that is not guaranteed to find the optimal solution, but is designed to find a satisfactory solution in a reasonable amount of time. Heuristics are often used in artificial intelligence, search algorithms, and optimization problems where it is not possible or impractical to use an algorithm that guarantees a correct solution.

Heuristics are often based on experience, intuition, or common sense and are used to guide the search for a solution in a way that is efficient and effective. They can be useful in situations where the problem is too complex or too large to be solved by an algorithm that guarantees a correct solution.

Examples of heuristics in computer science include:

• Best-first search
• Hill climbing
• Simulated annealing
• Genetic algorithms

Heuristics can be very useful in computer science, they can be faster and more efficient than other techniques, but they are also less reliable and might not provide optimal solutions.

In computer science, artificial intelligence , and mathematical optimization, a heuristic is a technique designed for solving a problem more quickly when classic methods are too slow or for finding an approximate solution when classic methods fail to find any exact solution. This is achieved by trading optimality, completeness, accuracy, or precision for speed. 

Heuristic programming employs a practical method, not guaranteed to be optimal, perfect, logical, or rational, but instead sufficient for reaching an immediate goal. It is important to highlight that Heuristics are the strategies derived from previous experiences with similar problems. These strategies rely on using readily accessible, though loosely applicable, information to control problem-solving in human beings, machines, and abstract issues.  And the objective of a heuristic is to produce a solution in a reasonable time frame that is good enough for solving the problem at hand. 

The trade-off criteria for deciding whether to use a heuristic for solving a given problem:

• Optimality: When several solutions exist for a given problem, does the heuristic guarantee that the best solution will be found? Is it actually necessary to find the best solution?
• Completeness: When several solutions exist for a given problem, can the heuristic find them all? Do we actually need all solutions? Many heuristics are only meant to find one solution.
• Accuracy and precision: Can the heuristic provide a confidence interval for the purported solution? Is the error bar on the solution unreasonably large?
• Execution time: Is this the best-known heuristic for solving this type of problem? Some heuristics converge faster than others. Some heuristics are only marginally quicker than classic methods.

And now, the main question is: why do we rely on heuristics?  Psychologists have suggested a few different theories:

• Effort reduction: According to this theory, people utilize heuristics as a type of cognitive laziness. Heuristics reduce the mental effort required to make choices and decisions.
• Attribute substitution: Other theories suggest people substitute simpler but related questions in place of more complex and difficult questions.
• Fast and frugal: Still other theories argue that heuristics are actually more accurate than they are biased. In other words, we use heuristics because they are fast and usually correct.

This is in contrast to algorithmic programming, which is based on mathematically provable procedures. But what is important to understand here is that Heuristic programming is characterized by programs that are self-learning; they get better with experience. Remember, heuristics don't guarantee the best or perfect solution, but they often lead to good solutions in a reasonable time frame, which is why they're so widely used in computer science.

Let us know about your thoughts and experience with heuristic programming, we would be happy to discuss it in the comments section below. 

Reviewed by Psychology Today Staff

A heuristic is a mental shortcut that allows an individual to make a decision, pass judgment, or solve a problem quickly and with minimal mental effort. While heuristics can reduce the burden of decision-making and free up limited cognitive resources, they can also be costly when they lead individuals to miss critical information or act on unjust biases.

• Understanding Heuristics
• Different Heuristics
• Problems with Heuristics

As humans move throughout the world, they must process large amounts of information and make many choices with limited amounts of time. When information is missing, or an immediate decision is necessary, heuristics act as “rules of thumb” that guide behavior down the most efficient pathway.

Heuristics are not unique to humans; animals use heuristics that, though less complex, also serve to simplify decision-making and reduce cognitive load.

Generally, yes. Navigating day-to-day life requires everyone to make countless small decisions within a limited timeframe. Heuristics can help individuals save time and mental energy, freeing up cognitive resources for more complex planning and problem-solving endeavors.

The human brain and all its processes—including heuristics— developed over millions of years of evolution . Since mental shortcuts save both cognitive energy and time, they likely provided an advantage to those who relied on them.

Heuristics that were helpful to early humans may not be universally beneficial today . The familiarity heuristic, for example—in which the familiar is preferred over the unknown—could steer early humans toward foods or people that were safe, but may trigger anxiety or unfair biases in modern times.

The study of heuristics was developed by renowned psychologists Daniel Kahneman and Amos Tversky. Starting in the 1970s, Kahneman and Tversky identified several different kinds of heuristics, most notably the availability heuristic and the anchoring heuristic.

Since then, researchers have continued their work and identified many different kinds of heuristics, including:

Familiarity heuristic

Fundamental attribution error

Representativeness heuristic

Satisficing

The anchoring heuristic, or anchoring bias , occurs when someone relies more heavily on the first piece of information learned when making a choice, even if it's not the most relevant. In such cases, anchoring is likely to steer individuals wrong .

The availability heuristic describes the mental shortcut in which someone estimates whether something is likely to occur based on how readily examples come to mind . People tend to overestimate the probability of plane crashes, homicides, and shark attacks, for instance, because examples of such events are easily remembered.

People who make use of the representativeness heuristic categorize objects (or other people) based on how similar they are to known entities —assuming someone described as "quiet" is more likely to be a librarian than a politician, for instance. 

Satisficing is a decision-making strategy in which the first option that satisfies certain criteria is selected , even if other, better options may exist.

Heuristics, while useful, are imperfect; if relied on too heavily, they can result in incorrect judgments or cognitive biases. Some are more likely to steer people wrong than others.

Assuming, for example, that child abductions are common because they’re frequently reported on the news—an example of the availability heuristic—may trigger unnecessary fear or overprotective parenting practices. Understanding commonly unhelpful heuristics, and identifying situations where they could affect behavior, may help individuals avoid such mental pitfalls.

Sometimes called the attribution effect or correspondence bias, the term describes a tendency to attribute others’ behavior primarily to internal factors—like personality or character— while attributing one’s own behavior more to external or situational factors .

If one person steps on the foot of another in a crowded elevator, the victim may attribute it to carelessness. If, on the other hand, they themselves step on another’s foot, they may be more likely to attribute the mistake to being jostled by someone else .

Listen to your gut, but don’t rely on it . Think through major problems methodically—by making a list of pros and cons, for instance, or consulting with people you trust. Make extra time to think through tasks where snap decisions could cause significant problems, such as catching an important flight.

Psychological experiments on human judgment under uncertainty showed that people often stray from presumptions about rational economic agents.

Psychology, like other disciplines, uses the scientific method to acquire knowledge and uncover truths—but we still ask experts for information and rely on intuition. Here's why.

We all experience these 3 cognitive blind spots at work, frequently unaware of their costs in terms of productivity and misunderstanding. Try these strategies to work around them.

Have you ever fallen for fake news? This toolkit can help you easily evaluate whether a claim is real or phony.

An insidious form of prejudice occurs when a more powerful group ignores groups with less power and keeps them out of the minds of society.

Chatbot designers engage in dishonest anthropomorphism by designing features to exploit our heuristic processing and dupe us into overtrusting and assigning moral responsibility.

How do social media influencers convert a scroll into a like, follow, and sale? Here are the psychological principles used by digital influencers.

Sometimes, we submit to the oppressive aspects of life voluntarily, by accepting them as fixed and immutable even when they are not. We fall into a mental trap. Why?

Despite the bombardment of societal messages to never quit, sometimes changing course is exactly what you should do.

Many have experienced the "Mandela Effect." Some believe that the past has been subtly changed or that we live in a divergent reality. Here's what psychology has to say.

• Find a Therapist
• Find a Treatment Centre
• Find Online Therapy
• Calgary, AB
• Edmonton, AB
• Hamilton, ON
• Montréal, QC
• Toronto, ON
• Vancouver, BC
• Winnipeg, MB
• Mississauga, ON
• Oakville, ON
• Asperger's
• Bipolar Disorder
• Chronic Pain
• Eating Disorders
• Passive Aggression
• Personality
• Goal Setting
• Positive Psychology
• Stopping Smoking
• Low Sexual Desire
• Relationships
• Child Development
• Therapy Center NEW
• Diagnosis Dictionary
• Types of Therapy

Understanding what emotional intelligence looks like and the steps needed to improve it could light a path to a more emotionally adept world.

• Coronavirus Disease 2019
• Affective Forecasting
• Neuroscience

Thinking and Intelligence

Solving Problems

Learning objectives.

• Describe problem solving strategies, including algorithms and heuristics

People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe be doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

Problem-Solving Strategies

When you are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

A problem-solving strategy is a plan of action used to find a solution. Different strategies have different action plans associated with them. For example, a well-known strategy is trial and error . The old adage, “If at first you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

Another type of strategy is an algorithm. An algorithm is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backwards is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C. and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backwards heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

What problem-solving method could you use to solve Einstein’s famous riddle?

https://youtube.com/watch?v=1rDVz_Fb6HQ%3Flist%3DPLUmyCeox8XCwB8FrEfDQtQZmCc2qYMS5a

You can view the transcript for “Can you solve “Einstein’s Riddle”? – Dan Van der Vieren” here (opens in new window) .

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

Everyday Connections: Solving Puzzles

Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below (Figure 1) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

Here is another popular type of puzzle that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Take a look at the “Puzzling Scales” logic puzzle below (Figure 3). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

Were you able to determine how many marbles are needed to balance the scales in the Puzzling Scales? You need nine. Were you able to solve the other problems above? Here are the answers:

CC licensed content, Original

• Modification and adaptation. Provided by : Lumen Learning. License : CC BY: Attribution

CC licensed content, Shared previously

• Problem-Solving. Authored by : OpenStax College. Located at : https://openstax.org/books/psychology-2e/pages/7-3-problem-solving . License : CC BY: Attribution . License Terms : Download for free at https://openstax.org/books/psychology-2e/pages/1-introduction

All rights reserved content

• Can you solve Einsteinu2019s Riddle? . Authored by : Dan Van der Vieren. Provided by : Ted-Ed. Located at : https://www.youtube.com/watch?v=1rDVz_Fb6HQ&index=3&list=PLUmyCeox8XCwB8FrEfDQtQZmCc2qYMS5a . License : Other . License Terms : Standard YouTube License

method for solving problems

problem-solving strategy in which multiple solutions are attempted until the correct one is found

problem-solving strategy characterized by a specific set of instructions

mental shortcut that saves time when solving a problem

heuristic in which you begin to solve a problem by focusing on the end result

General Psychology Copyright © by OpenStax and Lumen Learning is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

Share This Book

Heuristics in Mathematics Education

• Reference work entry
• First Online: 01 January 2020
• Cite this reference work entry

• Nicholas Mousoulides 2 &
• Bharath Sriraman 3  

294 Accesses

3 Citations

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Durable hardcover edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Begle EG (1979) Critical variables in mathematics education. MAA & NCTM, Washington, DC

Google Scholar  

Burkhardt H (1988) Teaching problem solving. In: Burkhardt H, Groves S, Schoenfeld A, Stacey K (eds) Problem solving – a world view (Proceedings of the problem solving theme group, ICME 5). Shell Centre, Nottingham, pp 17–42

English L, Sriraman B (2010) Problem solving for the 21st century. In: Sriraman B, English L (eds) Theories of mathematics education: seeking new frontiers. Springer, Berlin, pp 263–290

Chapter   Google Scholar  

Goldin G (2010) Problem solving heuristics, affect, and discrete mathematics: a representational discussion. In: Sriraman B, English L (eds) Theories of mathematics education: seeking new frontiers. Springer, Berlin, pp 241–250

Polya G (1945) How to solve it. Princeton University Press, Princeton

Book   Google Scholar  

Polya G (1962) Mathematical discovery, vol 1. Wiley, New York

Polya G (1965) Mathematical discovery, vol 2. Wiley, New York

Schoenfeld A (1992) Learning to think mathematically: problem solving, metacognition, and sense making in mathematics. In: Grouws DA (ed) Handbook of research on mathematics teaching and learning. Macmillan, New York, pp 334–370

Sriraman B, English L (eds) (2010) Theories of mathematics education: seeking new frontiers (Advances in mathematics education). Springer, Berlin

Download references

Author information

Authors and affiliations.

University of Nicosia, Nicosia, Cyprus

Nicholas Mousoulides

Department of Mathematical Sciences, The University of Montana, Missoula, MT, USA

Bharath Sriraman

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Nicholas Mousoulides .

Editor information

Editors and affiliations.

Department of Education, Centre for Mathematics Education, London South Bank University, London, UK

Stephen Lerman

Section Editor information

Rights and permissions.

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this entry

Cite this entry.

Mousoulides, N., Sriraman, B. (2020). Heuristics in Mathematics Education. In: Lerman, S. (eds) Encyclopedia of Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-030-15789-0_172

Download citation

DOI : https://doi.org/10.1007/978-3-030-15789-0_172

Published : 23 February 2020

Publisher Name : Springer, Cham

Print ISBN : 978-3-030-15788-3

Online ISBN : 978-3-030-15789-0

eBook Packages : Education Reference Module Humanities and Social Sciences Reference Module Education

Share this entry

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research