Cold play: Learning across bimatrix games

Lensberg, Terje and Schenk-Hoppé, Klaus R. (2020): Cold play: Learning across bimatrix games.

Abstract

We study one-shot play in the set of all bimatrix games by a large population of agents. The agents never see the same game twice, but they can learn ‘across games’ by developing solution concepts that tell them how to play new games. Each agent’s individual solution concept is represented by a computer program, and natural selection is applied to derive stochastically stable solution concepts. Our aim is to develop a theory predicting how experienced agents would play in one-shot games.

• Item Type: MPRA Paper
• Language: English
• Keywords: One-shot games, solution concepts, genetic programming, evolutionary stability.
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; C - Mathematical and Quantitative Methods > C7 - Game Theory and Bargaining Theory > C73 - Stochastic and Dynamic Games ; Evolutionary Games ; Repeated Games; C - Mathematical and Quantitative Methods > C9 - Design of Experiments > C90 - General

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