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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… Click to show full 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.
Keywords:
cold play;
play;
play learning;
learning across;
bimatrix games
Journal Title: Journal of Economic Behavior and Organization
Year Published: 2021
Link to full text (if available)
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Journal Title: Journal of Economic Behavior and Organization
Year Published: 2021
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!