12.1 Cognitive limitations and decision-making biases
5 min read•july 30, 2024
Behavioral Game Theory explores how real people make decisions in strategic situations. It recognizes that we're not always perfectly rational. Instead, we use mental shortcuts and are influenced by emotions, leading to choices that don't always maximize our payoffs.
Cognitive limitations and biases play a big role in how we approach games. We might be overconfident, rely too much on one piece of info, or fall for the . Understanding these biases helps explain why people often deviate from what traditional game theory predicts.
Cognitive Biases in Game Theory
Common Biases and Heuristics
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- Cognitive biases lead to systematic deviations from rational decision-making and suboptimal choices in strategic interactions
- Common biases include , anchoring (relying too heavily on one piece of information), availability (overestimating the likelihood of events that are easily remembered), and representativeness (judging the probability of an event based on its resemblance to a typical case)
- Heuristics are mental shortcuts or rules of thumb that simplify complex decision problems but can lead to biased judgments
- Examples of heuristics are the (choosing the option that is more familiar), (making decisions based on the most important cue), and (allocating resources equally among options)
Framing Effects and Biases
- Framing effects happen when different presentations of the same information lead to changes in decisions
- explains how framing choices in terms of gains or losses affects risk preferences, with people being risk-averse for gains and risk-seeking for losses
- The sunk cost fallacy is continuing to invest in a losing course of action because of past unrecoverable investments, which can lead to an irrational escalation of commitment
- involves searching for, interpreting, and recalling information in a way that confirms preexisting beliefs while giving less attention to disconfirming evidence
- The is the belief that one can influence outcomes that are actually determined by chance, which leads to overestimation of success probabilities in many situations
Bounded Rationality in Games
Limitations and Satisficing Behavior
- recognizes that decision-makers face cognitive limitations and constraints on time, information, and computational capacity
- These limitations lead to (choosing an option that is good enough) rather than optimizing (choosing the best possible option) behavior
- Limited strategic thinking can be modeled using level-k reasoning, where level-0 players make non-strategic choices, level-1 players best respond to level-0, and so on
- Empirical evidence suggests that most people engage in only a few levels of reasoning, with level-1 and level-2 being most common
Alternative Equilibrium Concepts
- is a generalization of Nash equilibrium that allows for stochastic choice and bounded rationality by incorporating noise in best response functions
- This concept can better explain deviations from perfect rationality and the persistence of suboptimal strategies in some games
- assumes that players best respond to their beliefs about the distribution of other players' strategic sophistication levels
- This leads to different equilibrium predictions than standard models and can account for behavior in games like p-beauty contests
- Bounded rationality can lead to the use of or salient solutions in coordination games, even when they are not equilibria in the classical sense, due to their prominence or intuitive appeal
Limitations of Game Theory Models
Deviations from Rational Choice Theory
- Experimental studies have shown systematic deviations from the predictions of rational choice theory and Nash equilibrium in many games
- Examples include the ultimatum game (people reject unfair offers even though accepting any positive amount is a dominant strategy), centipede game (players cooperate more than predicted), and beauty contest game (choices are not based on higher-order reasoning)
- Models incorporating cognitive limitations and learning, such as (choosing strategies that have led to good outcomes in the past), (updating the attractiveness of strategies based on their past performance), and (balancing the impulse to choose each strategy based on its regret), can provide better explanations for observed behavior in games
Challenges for Classical Models
- Bounded rationality can lead to the persistence of dominated strategies and the failure to converge to Nash equilibria in some games, especially those with complex strategy spaces or dynamic structures
- Cognitive limitations can also affect the ability to engage in backward induction and subgame perfect reasoning, leading to deviations from theoretical predictions in sequential games like the ultimatum game and the trust game
- The predictive power of classical game theory models may be limited in situations where players have incomplete information about the game structure, payoffs, or other players' types and beliefs
- Incorporating uncertainty and learning into game-theoretic models can help to address these limitations and improve their descriptive accuracy
Emotions and Social Factors in Strategy
Emotions and Preferences
- Emotions such as anger, fear, and gratitude can influence risk attitudes, time preferences, and social preferences in ways that deviate from the predictions of purely rational models
- For example, anger can lead to more risk-seeking behavior, while gratitude can increase trust and reciprocity
- Social norms, fairness concerns, and reciprocity motives can lead to cooperative behavior in social dilemmas (situations where individual incentives conflict with collective interests) and ultimatum bargaining games, even when defection or selfishness is the unique Nash equilibrium
- Guilt aversion, the desire to avoid disappointing others' expectations, can sustain cooperation and trust in games such as the trust game (where one player can send money to another, who can then return some amount) and the promise game (where players can make non-binding commitments)
Social Identity and Framing
- Social identity and group membership can affect strategy choices and lead to in-group favoritism and out-group discrimination in competitive and cooperative games
- For instance, people may be more willing to cooperate with members of their own group and less willing to cooperate with outsiders
- Emotions and social preferences can be incorporated into game-theoretic models through modifications of utility functions, such as (disliking unequal outcomes), (caring about the payoffs of others), and (allowing payoffs to depend on beliefs and emotions)
- The presence of social cues and framing can activate norms and scripts that shape behavior in strategic interactions, leading to different outcomes than predicted by standard models
- For example, framing a prisoner's dilemma as a "community game" rather than a "Wall Street game" can lead to higher levels of cooperation by evoking different social norms and expectations
Key Terms to Review (25)
1/n heuristic: The 1/n heuristic is a decision-making shortcut where individuals divide their available resources equally among a number of options, often leading to suboptimal choices. This approach reflects cognitive limitations, as it simplifies complex decision-making processes by relying on equal distribution rather than a more nuanced evaluation of each option's potential value. It highlights how biases and limited information can shape decisions in uncertain environments.
Amos Tversky: Amos Tversky was a pioneering psychologist known for his groundbreaking work in behavioral economics and cognitive psychology, particularly in the study of decision-making and heuristics. His research, often in collaboration with Daniel Kahneman, highlighted how cognitive limitations lead to systematic biases in human judgment and decision-making processes.
Anchoring Bias: Anchoring bias is a cognitive bias that occurs when individuals rely too heavily on the first piece of information they encounter (the 'anchor') when making decisions. This initial information sets a reference point, and subsequent judgments are influenced by this anchor, often leading to skewed or irrational conclusions. Anchoring bias can affect various aspects of decision-making, including pricing, negotiations, and estimations.
Availability heuristic: The availability heuristic is a mental shortcut that relies on immediate examples that come to a person's mind when evaluating a specific topic or decision. This cognitive bias can lead individuals to overestimate the importance or frequency of events based on how easily they can recall similar instances, which ultimately affects decision-making processes. It highlights cognitive limitations by illustrating how reliance on easily accessible information can skew perceptions and lead to flawed judgments.
Behavioral Economics: Behavioral economics is a field that combines insights from psychology and economics to understand how individuals make decisions that deviate from traditional economic theory. It highlights the influence of cognitive limitations and emotional factors on decision-making processes, emphasizing that people often act irrationally in predictable ways. This field also explores models of bounded rationality, which reflect how individuals learn and adapt their strategies in various scenarios, especially in games.
Bounded rationality: Bounded rationality refers to the idea that individuals, when making decisions, are limited by their cognitive abilities, available information, and time constraints. This concept highlights that humans often rely on simplifying strategies or heuristics rather than fully rational approaches, leading to decisions that may not always align with traditional economic models of rational choice.
Cognitive Hierarchy Theory: Cognitive hierarchy theory is a framework that explains how individuals make decisions in strategic situations by considering the level of thinking or reasoning of others involved. It posits that people can be categorized into different levels of thinking, with each level representing a different degree of awareness regarding the thought processes and strategies of others. This theory is particularly relevant in understanding cognitive limitations and decision-making biases, as it highlights how individuals often rely on simplified models of others' behavior rather than fully comprehending their strategies.
Confirmation bias: Confirmation bias is the tendency for individuals to favor information that confirms their preexisting beliefs while disregarding or undervaluing evidence that contradicts those beliefs. This cognitive limitation can significantly impact decision-making processes, leading to skewed perceptions and irrational choices.
Daniel Kahneman: Daniel Kahneman is a renowned psychologist known for his groundbreaking work in behavioral economics and decision-making, particularly regarding how people perceive risk and make choices under uncertainty. His research has profoundly influenced the understanding of human behavior, revealing that individuals often rely on cognitive shortcuts, leading to systematic biases in judgment and decision-making.
Experience-weighted attraction: Experience-weighted attraction is a concept in game theory that describes how individuals adjust their preferences based on their past experiences in decision-making scenarios. This approach helps to model how players learn over time, as they weigh their experiences more heavily when determining which strategies to adopt, leading to more refined decision-making. By considering both successful and unsuccessful outcomes, players can update their strategies and adapt to changing environments in games.
Focal Points: Focal points are solutions or strategies in game theory that players naturally gravitate towards in situations where multiple equilibria exist. These points help guide decision-making when players have to coordinate their actions without explicit communication, relying on shared expectations or common knowledge to determine the most salient choice.
Illusion of control: The illusion of control refers to the tendency of individuals to overestimate their ability to influence events, particularly in situations that are actually determined by chance. This cognitive bias can lead people to believe they have more control over outcomes than they realistically do, often affecting their decision-making processes and judgments. It plays a significant role in various aspects of life, including gambling, investment choices, and even day-to-day activities.
Impulse Balance Theory: Impulse Balance Theory is a concept that suggests decision-making processes are influenced by the interplay between impulsive and reflective cognitive processes. This theory highlights how individuals often rely on quick, intuitive judgments driven by immediate emotions or urges, which can lead to biases and errors in decision-making, especially when cognitive limitations come into play.
Inequality aversion: Inequality aversion refers to the preference for fair distribution of resources or outcomes, where individuals have a strong dislike for unequal allocations. This concept highlights that people often experience discomfort or dissatisfaction when they perceive unequal treatment or outcomes, even if it doesn't directly affect their own situation. Inequality aversion plays a crucial role in shaping social preferences and influences decision-making in various contexts, as individuals tend to favor actions that promote fairness and equity over those that maximize their own benefits.
Overconfidence: Overconfidence is a cognitive bias that leads individuals to overestimate their knowledge, abilities, or the accuracy of their predictions. This tendency can skew decision-making processes, resulting in poor outcomes due to an inflated sense of certainty about one's judgments. It often manifests in various scenarios, affecting personal, professional, and social decisions.
Prospect Theory: Prospect Theory is a behavioral economic theory that describes how individuals evaluate potential losses and gains when making decisions under risk. It suggests that people are more sensitive to potential losses than to equivalent gains, which leads to behaviors that deviate from traditional expected utility theory. This theory highlights how cognitive biases and emotional reactions can influence decision-making processes, particularly in uncertain situations.
Psychological Game Theory: Psychological game theory is a branch of game theory that incorporates the psychological factors and emotional motivations influencing decision-making in strategic interactions. This approach recognizes that players do not always act solely based on material payoffs but are also influenced by their beliefs, emotions, and social preferences, which can lead to cognitive limitations and decision-making biases.
Quantal response equilibrium: Quantal response equilibrium is a solution concept in game theory that generalizes Nash equilibrium by incorporating the idea that players may make decisions based on probabilistic responses to their opponents' strategies. In this framework, players' actions are influenced by their beliefs about others’ strategies and the cognitive limitations they face, leading to stochastic choices rather than deterministic ones. This concept connects to decision-making biases, computational complexity, and models of bounded rationality as it reflects how real-world decision-making often deviates from perfect rationality.
Recognition Heuristic: The recognition heuristic is a mental shortcut that suggests people tend to favor information that they recognize over information they do not, especially when making decisions under uncertainty. This bias can lead to choices based on familiarity rather than objective analysis, highlighting cognitive limitations in decision-making processes. It demonstrates how recognition can serve as a proxy for quality or relevance, often resulting in systematic biases.
Reinforcement Learning: Reinforcement learning is a type of machine learning where an agent learns to make decisions by taking actions in an environment to maximize cumulative rewards over time. This learning process involves exploration and exploitation, where the agent must balance trying new actions and using known ones that yield high rewards. It's deeply tied to concepts of decision-making biases and cognitive limitations, as well as applications in AI, especially when multiple agents interact with each other in complex environments.
Representativeness heuristic: The representativeness heuristic is a cognitive shortcut that people use to make judgments about the likelihood of an event based on how closely it resembles a typical case. This mental model often leads individuals to ignore statistical reasoning and rely on stereotypes or pre-existing notions, resulting in biased decision-making.
Satisficing: Satisficing is a decision-making strategy that aims for a satisfactory or adequate result, rather than the optimal one. It reflects the idea that individuals often settle for a choice that meets their minimum requirements due to constraints like limited information, time, or cognitive resources. This approach recognizes the challenges in achieving perfect rationality and highlights how people navigate complex decisions by choosing options that are 'good enough' instead of the best possible.
Social welfare preferences: Social welfare preferences refer to the collective preferences of individuals in a society regarding the distribution of resources, opportunities, and well-being among its members. These preferences shape how policies are designed and evaluated, as they reflect societal values about fairness, equity, and efficiency. Understanding social welfare preferences is crucial because they influence decision-making processes that ultimately affect everyone in the community.
Sunk cost fallacy: The sunk cost fallacy is a cognitive bias where individuals continue an endeavor or commitment due to previously invested resources (time, money, effort), rather than assessing the current situation objectively. This fallacy often leads to poor decision-making because people struggle to disregard past investments, even when they no longer justify further expenditures. Essentially, it can distort rational judgment by making individuals stick with losing propositions.
Take-the-best heuristic: The take-the-best heuristic is a decision-making strategy that simplifies the process by focusing on the most important cue to make a choice, ignoring other potentially relevant information. This method is grounded in cognitive psychology and reflects how people often rely on a single, dominant factor to guide their decisions, which can lead to biases and suboptimal outcomes. It highlights the cognitive limitations individuals face when processing complex information and illustrates how biases can emerge from relying on simplified decision rules.