Learning by Imitation in Games: Theory, Field, and Laboratory

Erik Mohlin (), Robert Östling and Joseph Wang

No 734, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: We exploit a unique opportunity to study how a large population of players in the field learn to play a novel game with a complicated and non-intuitive mixed strategy equilibrium. We argue that standard models of belief-based learning and reinforcement learning are unable to explain the data, but that a simple model of similarity-based global cumulative imitation can do so. We corroborate our findings using laboratory data from a scaled-down version of the same game, as well as from three other games. The theoretical properties of the proposed learning model are studied by means of stochastic approximation.

Keywords: Learning; imitation; behavioral game theory; evolutionary game theory; stochastic approximation; replicator dynamic; similarity-based reasoning; generalization; mixed equilibrium (search for similar items in EconPapers)
JEL-codes: C72 C73 L83 (search for similar items in EconPapers)
Date: 2014-11-28
New Economics Papers: this item is included in nep-cbe and nep-gth
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Citations: View citations in EconPapers (3)

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