Studying Cognition via Information Search in Game Experiments

通过游戏实验中的信息搜索研究认知

• 批准号: 0100072
• 负责人: Vincent Crawford
• 金额: $ 24.56万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-01 至 2005-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0100072&HistoricalAwards=false
• 关键词: Studying; Cognition; via; Information; Search

Many unresolved questions about strategic behavior concern strategic sophistication, the extent to which players analyze their environment as a game, taking its structure and others' incentives into account. Sophistication is the main difference between the behavioral assumptions of traditional game theory, which take it to be unlimited, and adaptive learning models, which take it to be nonexistent or severely limited. It is also the main difference between the leading kinds of learning models, beliefs-based and reinforcement. Even when convergence to equilibrium is assured, sophistication can affect limiting outcomes through players' initial beliefs and the structure of their learning rules. The influence of sophistication on convergence, equilibrium selection, and the nature and timing of responses to changes in the environment give it a leading role in applications of game theory to economic, political, and social interactions.This project concerns experiments designed and conducted with Faculty Associate Miguel Costa-Gomes of the University of York, UK. Experiments allow the control needed to test theories of behavior in games, which are sensitive to environmental details. Experiments also allow us to study sophistication and other aspects of cognition more directly, by monitoring subjects' searches for hidden information. Under plausible assumptions about cognition and information search, leading theories of initial decisions and of learning both have sharply separated implications for search. Interpreting subjects' searches in the light of the cognitive implications of alternative theories of behavior help to understand their strategic thinking and predict their behavior.Some experiments adapt the MouseLab design used to study subjects' initial responses to two-person matrix games to two-person guessing games in which subjects have hidden, independently variable payoff parameters, monitoring their searches for their own and their partners' parameters. This new design better separates decision rules; and searching for payoff parameters within a known structure is a very different cognitive task than searching directly for payoffs in matrix games, which expands our view of subjects' strategic thinking. Another set of MouseLab experiments adapts our previous design to study initial responses to two-person matrix games with multiple equilibria mixed with other games designed to separate boundedly rational decision rules. The main goal is to separate traditional theories of equilibrium selection that apply notions like risk- or payoff-dominance to the set of equilibria from the view that responses to games with multiple equilibria are a by-product of the same kinds of boundedly rational rules that appear to predominate in other games. A third set of experiments monitor subjects' searches for hidden payoff parameters and the history of decisions and realized payoffs in repeated play of normal-form games with a variety of structures. The goal is to exploit sharp separation of information requirements to distinguish reinforcement and beliefs-based learning and hybrids such as experience-weighted attraction learning. These experiments require the development of a new interface with expanded search capabilities.

关于策略行为的许多未解决的问题都与策略复杂性有关，即玩家将环境作为游戏来分析的程度，将其结构和其他动机考虑在内。传统博弈论的行为假设认为它是无限的，而适应性学习模型认为它是不存在或严重有限的，复杂程度是这两者之间的主要区别。这也是基于信念的学习模式和强化学习模式这两种主要学习模式之间的主要区别。即使趋同于平衡是确定的，复杂性也会通过玩家的初始信念和他们的学习规则结构影响有限的结果。复杂性对趋同、均衡选择以及对环境变化的反应的性质和时机的影响，使其在将博弈论应用于经济、政治和社会互动方面发挥了主导作用。该项目涉及与英国约克大学的Miguel Costa-Gomes教授合作设计和实施的实验。实验允许测试对环境细节敏感的游戏行为理论所需的控制。通过监测实验对象对隐藏信息的搜索，实验还使我们能够更直接地研究复杂性和认知的其他方面。在关于认知和信息搜索的合理假设下，关于初始决策和学习的主要理论对搜索有着截然不同的含义。从行为替代理论的认知含义来解释被试的搜索行为有助于理解被试的策略思维和预测被试的行为。一些实验将用于研究受试者对两人矩阵游戏的初始反应的MouseLab设计改编为两人猜谜游戏，在猜谜游戏中，受试者有隐藏的、独立可变的收益参数，监测他们对自己和同伴参数的搜索。这种新设计更好地分离了决策规则；在已知结构中寻找收益参数与在矩阵游戏中直接寻找收益是非常不同的认知任务，后者扩展了我们对受试者战略思维的看法。另一组MouseLab实验采用了我们之前的设计，研究了具有多重均衡的两人矩阵博弈的初始反应，并混合了其他旨在分离有界理性决策规则的博弈。其主要目标是将传统的均衡选择理论（将风险或收益优势等概念应用于均衡集）与对具有多个均衡的博弈的反应是在其他博弈中占主导地位的有限理性规则的副产品的观点区分开来。第三组实验监测受试者在各种结构的标准形式游戏中对隐藏收益参数和决策历史的搜索以及实现收益。目标是利用信息需求的尖锐分离来区分强化和基于信念的学习以及混合学习，如经验加权吸引学习。这些实验需要开发具有扩展搜索功能的新界面。