Learning by similarity-weighted imitation in winner-takes-all games

Erik Mohlin (), Robert Östling and Joseph Wang

Games and Economic Behavior, 2020, vol. 120, issue C, 225-245

Abstract: We study a simple model of similarity-based global cumulative imitation in symmetric games with large and ordered strategy sets and a salient winning player. We show that the learning model explains behavior well in both field and laboratory data from one such “winner-takes-all” game: the lowest unique positive integer game in which the player that chose the lowest number not chosen by anyone else wins a fixed prize. We corroborate this finding in three other winner-takes-all games and discuss under what conditions the model may be applicable beyond this class of games. Theoretically, we show that global cumulative imitation without similarity weighting results in a version of the replicator dynamic in winner-takes-all games.

Keywords: Learning; Imitation; Behavioral game theory; Evolutionary game theory; Stochastic approximation; Replicator dynamic; Similarity-based reasoning; Beauty contest; Lowest unique positive integer game; Mixed equilibrium (search for similar items in EconPapers)
JEL-codes: C72 C73 L83 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:gamebe:v:120:y:2020:i:c:p:225-245

DOI: 10.1016/j.geb.2019.12.008

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