5 min read•Last Updated on July 30, 2024
Strategic decision-making and rational choice form the backbone of game theory. These concepts explore how players make choices to maximize their outcomes, considering the actions of others and available information.
Understanding these principles is crucial for analyzing strategic interactions. By examining assumptions of rationality, types of games, and concepts like dominance and Nash equilibrium, we gain insights into predicting behavior in competitive situations.
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The Decision Making Process | Organizational Behavior and Human Relations View original
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The Shape of Rational Choices in Game Theory - Dr Tarun Sabarwal, University of Kansas • scipod ... View original
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The Decision Making Process | Organizational Behavior and Human Relations View original
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The Shape of Rational Choices in Game Theory - Dr Tarun Sabarwal, University of Kansas • scipod ... View original
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Rational Decision Making vs. Other Types of Decision Making | Principles of Management View original
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The Decision Making Process | Organizational Behavior and Human Relations View original
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Altruism refers to the selfless concern for the well-being of others, often manifesting as acts of kindness or generosity without expectation of personal gain. This concept plays a significant role in understanding how individuals make decisions that impact both themselves and others, particularly in scenarios where cooperation and social interactions are involved. Altruism can challenge traditional notions of rational choice by introducing the idea that people may act against their own self-interest for the sake of others.
Term 1 of 29
Altruism refers to the selfless concern for the well-being of others, often manifesting as acts of kindness or generosity without expectation of personal gain. This concept plays a significant role in understanding how individuals make decisions that impact both themselves and others, particularly in scenarios where cooperation and social interactions are involved. Altruism can challenge traditional notions of rational choice by introducing the idea that people may act against their own self-interest for the sake of others.
Term 1 of 29
Altruism refers to the selfless concern for the well-being of others, often manifesting as acts of kindness or generosity without expectation of personal gain. This concept plays a significant role in understanding how individuals make decisions that impact both themselves and others, particularly in scenarios where cooperation and social interactions are involved. Altruism can challenge traditional notions of rational choice by introducing the idea that people may act against their own self-interest for the sake of others.
Term 1 of 29
Rationality refers to the principle of making decisions based on logic, consistent preferences, and maximizing utility. It is the foundation of strategic decision-making, where individuals or entities choose actions that lead to the best possible outcomes based on their preferences and available information. Understanding rationality helps explain behaviors in various contexts, such as predicting responses in strategic interactions and assessing the effectiveness of different strategies.
Utility: A measure of satisfaction or benefit derived from consuming goods and services, which individuals seek to maximize through their choices.
Nash Equilibrium: A situation in a strategic game where no player can benefit by changing their strategy while the other players keep theirs unchanged, indicating a state of mutual best responses.
Payoff Matrix: A table that describes the potential outcomes of strategic interactions, detailing the payoffs for each player based on the chosen strategies.
Nash equilibrium is a concept in game theory where no player can benefit from changing their strategy while the other players keep theirs unchanged. This situation arises when each player's strategy is optimal given the strategies of all other players, leading to a stable state in strategic interactions.
Dominant strategy: A strategy that is the best choice for a player, regardless of what the other players do.
Payoff matrix: A table that illustrates the payoffs for each player based on the strategies chosen in a game.
Subgame perfect equilibrium: An extension of Nash equilibrium that applies to extensive form games, ensuring that players' strategies constitute a Nash equilibrium in every subgame.
Expected payoff refers to the anticipated return or benefit from a decision or strategy in a game, calculated as a weighted average of all possible outcomes, each multiplied by its probability of occurring. This concept helps decision-makers evaluate the potential effectiveness of different strategies based on their likelihood of success and associated rewards. Understanding expected payoff is crucial for rational decision-making and optimizing strategies, especially when dealing with uncertainty and competitive environments.
Utility: A measure of satisfaction or value derived from a particular outcome or choice, often used in decision-making to assess preferences.
Risk Assessment: The process of identifying and analyzing potential events that may negatively impact individuals or organizations, helping to understand the likelihood and consequences of various risks.
Nash Equilibrium: A situation in a game where no player can benefit by changing their strategy while the other players keep theirs unchanged, indicating stable outcomes based on expected payoffs.
In game theory, a best response is the strategy that provides the highest payoff for a player, given the strategies chosen by other players. This concept is crucial because it helps players make rational choices based on their expectations of others' behavior, connecting to the broader themes of strategic decision-making and rational choice. Understanding best responses is essential for analyzing both pure and mixed strategies, determining optimal actions in normal form games, and finding Nash equilibria within those frameworks.
Nash Equilibrium: A situation in a game where no player can benefit from changing their strategy while the other players keep theirs unchanged, indicating that each player's strategy is a best response to the strategies of others.
Payoff Matrix: A table that illustrates the payoffs for each player based on the combinations of strategies chosen in a game, helping to determine best responses and outcomes.
Mixed Strategy: A strategy where a player randomizes over two or more actions rather than consistently choosing a single action, often used when no pure strategy Nash equilibrium exists.
Perfect information is a situation in a game where all players have complete knowledge of the actions, payoffs, and strategies available to them and other players at every point in the game. This level of transparency allows for strategic decision-making based on the full set of available data, leading players to make rational choices that can be predicted based on this information. Perfect information is a critical concept in understanding strategic interactions and analyzing equilibrium states, as it ensures that players can foresee the consequences of their actions in various scenarios.
Incomplete Information: A scenario where players do not have full knowledge of relevant aspects of the game, such as other players' types, strategies, or payoffs, often leading to uncertainty in decision-making.
Nash Equilibrium: A situation in a game where no player can benefit by changing their strategy while the other players keep theirs unchanged; it represents a state of balance in strategic interactions.
Extensive Form Game: A representation of a game that captures the sequential nature of decision-making among players, typically illustrated with a tree diagram showing possible moves and outcomes.
Incomplete information refers to a situation in game theory where players do not possess full knowledge about certain aspects of the game, such as other players' payoffs, strategies, or types. This uncertainty significantly impacts strategic decision-making and can lead to different outcomes compared to scenarios with complete information, as players must often rely on beliefs or probabilities to make their choices.
Types: The various characteristics or attributes of players in a game that may be private information, influencing their strategies and potential payoffs.
Belief System: A framework that represents a player's beliefs about other players' types and strategies, often formalized using probabilities in Bayesian games.
Bayesian Nash Equilibrium: A refinement of Nash Equilibrium that applies to games with incomplete information, where players choose strategies that are optimal given their beliefs about other players' types.
A dominant strategy is a course of action that yields a better outcome for a player, regardless of the actions chosen by other players. This concept highlights how players can make decisions based on their own best interests, which often leads to predictable behavior in strategic settings.
Nash equilibrium: A situation in a game where no player can benefit by changing their strategy while the other players keep theirs unchanged.
Payoff matrix: A table that represents the possible outcomes of a strategic interaction between players, showing the payoffs for each combination of strategies.
Mixed strategy: A strategy in which a player randomizes over possible moves, choosing different actions with specific probabilities to keep opponents uncertain.
Iterative elimination is a method used in game theory to systematically remove dominated strategies from consideration, thereby simplifying the strategic decision-making process. This technique helps players focus on more viable strategies by identifying options that are never optimal, allowing for a clearer understanding of rational choice in competitive situations.
Dominated Strategy: A strategy is dominated if there exists another strategy that always provides a better payoff, regardless of what the opponent does.
Nash Equilibrium: A situation in a game where no player can gain by unilaterally changing their strategy, as every player's strategy is optimal given the strategies of others.
Best Response: The strategy that yields the highest payoff for a player, given the strategies chosen by other players in the game.
The prisoner's dilemma is a standard example in game theory that illustrates a situation where two individuals must choose between cooperation and betrayal, leading to outcomes that are suboptimal for both. It showcases how rational decision-making can lead to a worse collective outcome when individuals act in their self-interest rather than cooperating.
Nash Equilibrium: A situation in a game where no player can benefit by changing their strategy while the other players keep theirs unchanged, often illustrated in the context of the prisoner's dilemma.
Cooperative Game: A type of game where players can benefit from cooperating and forming coalitions, contrasting with the non-cooperative nature of the prisoner's dilemma.
Dominant Strategy: A strategy that is optimal for a player regardless of what the other player does, which plays a crucial role in understanding decisions within the prisoner's dilemma.
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.
Heuristics: Mental shortcuts or rules of thumb that simplify decision-making processes, often used when individuals face complex choices.
Utility Maximization: The assumption in classical economics that individuals seek to maximize their satisfaction or benefit from choices based on complete information.
Satisficing: A decision-making strategy that aims for a satisfactory or adequate result rather than the optimal one, often used when individuals face bounded rationality.
Heuristics are mental shortcuts or rules of thumb that simplify decision-making processes and help individuals make judgments quickly without exhaustive analysis. These cognitive strategies can be especially useful in situations where time is limited, or information is incomplete, making them valuable in strategic decision-making and rational choice scenarios. However, while heuristics can lead to quick solutions, they may also introduce biases and errors, particularly when individuals rely on them in complex situations like algorithmic game theory.
Cognitive Bias: A systematic pattern of deviation from norm or rationality in judgment, often influenced by heuristics.
Bounded Rationality: A concept suggesting that individuals make decisions based on limited information and cognitive resources, often leading to satisficing rather than optimizing.
Game Theory: A mathematical framework for modeling scenarios in which conflicts of interest exist, often analyzed through the lens of strategy and decision-making.
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.
Bounded Rationality: A concept that suggests individuals are limited in their decision-making abilities due to constraints in knowledge, cognitive capacity, and time.
Optimal Decision-Making: The process of choosing the best possible option among available alternatives based on defined criteria and maximizing desired outcomes.
Heuristics: Mental shortcuts or rules of thumb that simplify decision-making processes, often used when facing complex problems or uncertainty.
Cognitive biases are systematic patterns of deviation from norm or rationality in judgment, which can influence the way individuals perceive and interpret information. These biases often lead to errors in thinking and decision-making, impacting how people assess risks and make strategic choices. Understanding cognitive biases is crucial as they can affect the outcomes of strategic decision-making and rational choice processes.
Heuristics: Mental shortcuts or rules of thumb that simplify decision-making but can lead to cognitive biases.
Confirmation bias: The tendency to search for, interpret, and remember information that confirms one’s preexisting beliefs while ignoring contradictory evidence.
Framing effect: A cognitive bias where people react to a particular choice based on how it is presented, rather than on the choice itself.
Social norms are the unwritten rules and expectations that govern the behavior of individuals within a society or group. They influence how people make decisions and interact with each other, often serving as a guide for what is considered acceptable or unacceptable behavior in various contexts. These norms play a crucial role in shaping strategic decision-making, as individuals often weigh their choices against societal expectations and the potential consequences of deviating from these norms.
Conformity: The act of matching attitudes, beliefs, and behaviors to group norms or expectations, often driven by social pressure.
Collective Behavior: The actions and conduct of a group of people, typically in situations where the group exhibits a shared identity or common goal.
Game Theory: A mathematical framework used to model strategic interactions among rational decision-makers, where social norms can influence the strategies chosen.
Altruism refers to the selfless concern for the well-being of others, often manifesting as acts of kindness or generosity without expectation of personal gain. This concept plays a significant role in understanding how individuals make decisions that impact both themselves and others, particularly in scenarios where cooperation and social interactions are involved. Altruism can challenge traditional notions of rational choice by introducing the idea that people may act against their own self-interest for the sake of others.
Cooperation: Cooperation is the process where individuals work together to achieve a common goal, often involving mutual benefit and shared resources.
Reciprocal Altruism: Reciprocal altruism is a theory suggesting that individuals may perform altruistic acts with the expectation that the favor will be returned in the future, fostering cooperative relationships.
Social Dilemma: A social dilemma is a situation where individual rationality leads to a collective outcome that is not optimal, often causing conflict between personal interests and group welfare.
Reciprocity refers to a social norm or principle in which individuals respond to each other in a mutual way, often by returning favors or actions. This concept is crucial for building trust and cooperation among individuals, especially in strategic interactions where the behavior of one participant influences the decisions of others. Understanding reciprocity helps explain how cooperation can emerge and be sustained in various situations, as it fosters an environment where parties are motivated to maintain positive interactions based on past behaviors.
Cooperation: A behavior where individuals work together towards a common goal, often seen in games where mutual benefits can be achieved.
Tit-for-Tat: A strategy in game theory where a player responds to an opponent's previous action with the same action, promoting reciprocity and cooperation.
Trust: The belief in the reliability and integrity of others, which is fundamental for forming reciprocal relationships and facilitating cooperation.
Bayesian games are a type of strategic game where players have incomplete information about other players' characteristics, such as their types, preferences, or available strategies. In these games, players must form beliefs about the unknown aspects and make decisions based on those beliefs, often leading to different strategies compared to games with complete information.
Incomplete Information: A situation in which players do not have full knowledge about the other players' characteristics or strategies, affecting their decision-making processes.
Types: The private information each player has about themselves, which influences their strategies and decisions in Bayesian games.
Bayes' Theorem: A mathematical formula that allows players to update their beliefs about the probability of other players' types based on new information or actions observed.
Evolutionary game theory is a framework that extends classical game theory to include the dynamics of strategy change over time, focusing on how organisms adapt their strategies based on interactions with others in their environment. This approach emphasizes the importance of evolutionary stability and how strategies evolve in populations, providing insights into strategic decision-making and rational choice in various contexts.
Evolutionarily Stable Strategy (ESS): A strategy that, if adopted by a population, cannot be invaded by any alternative strategy, maintaining its stability over time.
Natural Selection: The process through which organisms better adapted to their environment tend to survive and produce more offspring, influencing the evolution of strategies in a population.
Cooperative Game Theory: A branch of game theory that studies how cooperation among players can lead to mutually beneficial outcomes, often contrasting with the competitive nature of traditional game theory.