The Speed of Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation
Author(s) -
Yoella BerebyMeyer,
Alvin E. Roth
Publication year - 2006
Publication title -
american economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.936
H-Index - 297
eISSN - 1944-7981
pISSN - 0002-8282
DOI - 10.1257/aer.96.4.1029
Subject(s) - randomness , economics , stochastic game , reinforcement learning , repeated game , reinforcement , microeconomics , prisoner's dilemma , dilemma , action (physics) , constant (computer programming) , mathematical economics , computer science , psychology , game theory , social psychology , artificial intelligence , mathematics , statistics , physics , geometry , quantum mechanics , programming language
In an experiment, players? ability to learn to cooperate in the repeated prisoner?s dilemma was substantially diminished when the payoffs were noisy, even though players could monitor one another?s past actions perfectly. In contrast, in one-time play against a succession of opponents, noisy payoffs increased cooperation, by slowing the rate at which cooperation decays. These observations are consistent with the robust observation from the psychology literature that partial reinforcement (adding randomness to the link between an action and its consequences while holding expected payoffs constant) slows learning. This effect is magnified in the repeated game: when others are slow to learn to cooperate, the benefits of cooperation are reduced, which further hampers cooperation. These results show that a small change in the payoff environment, which changes the speed of individual learning, can have a large effect on collective behavior. And they show that there may be interesting comparative dynamics that can be derived from careful attention to the fact that at least some economic behavior is learned from experience. (JEL C71, C72, C73, D83)
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