Observability, dominance, and induction in learning models

• 成果类型: Article
• 署名作者: Clark, Daniel; Fudenberg, Drew; He, Kevin
• 署名单位: Yale University; Massachusetts Institute of Technology (MIT); University of Pennsylvania
• 刊物名称: JOURNAL OF ECONOMIC THEORY
• ISSN/ISSBN: 0022-0531
• DOI: 10.1016/j.jet.2022.105569
• 发表日期: 2022
• 关键词: Learning in games; Equilibrium refinements; Iterated dominance; forward induction

摘要

Learning models do not in general imply that weakly dominated strategies are irrelevant or justify the related concept of forward induction, because rational agents may use dominated strategies as experiments to learn how opponents play, and may not have enough data to rule out a strategy that opponents never use. Learning models also do not support the idea that the selected equilibria should only depend on a game's reduced normal form. However, playing the extensive form of a game is equivalent to playing the normal form augmented with the appropriate terminal node partitions so that two games are information equivalent, i.e., the players receive the same feedback about others' strategies.(c) 2022 Elsevier Inc. All rights reserved.