Observability, dominance, and induction in learning models

Daniel Clark, Drew Fudenberg and Kevin He

Journal of Economic Theory, 2022, vol. 206, issue C

Abstract: 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.

Keywords: Learning in games; Equilibrium refinements; Iterated dominance; Forward induction (search for similar items in EconPapers)
JEL-codes: C72 D83 (search for similar items in EconPapers)
Date: 2022
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Related works:
Working Paper: Observability, Dominance, and Induction in Learning Models (2022)
Working Paper: Observability, Dominance, and Induction in Learning Models (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:206:y:2022:i:c:s0022053122001594

DOI: 10.1016/j.jet.2022.105569

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