Games of Competition in a Stochastic Environment |
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Authors: | Judith?Avrahami Email author" target="_blank">Werner?GüthEmail author Yaakov?Kareev |
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Institution: | (1) Center for the Study of Rationality, and The Goldie Rotman Center for Cognitive Science and Education, The Hebrew University of Jerusalem, Jerusalem, Israel;(2) Max Planck Institute for Research into Economic Systems, Kahlaische Strasse 10, 07745 Jena, Germany |
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Abstract: | The paper presents a set of games of competition between two or three players in which reward is jointly determined by a stochastic
biased mechanism and players’ choices. More specifically, a resource can be found with unequal probabilities in one of two
locations. The first agent is rewarded only if it finds the resource and avoids being found by the next agent in line; the
latter is rewarded only if it finds the former. Five benchmarks, based on different psychological and game-theoretic assumptions
are derived and their predictions compared to actual behavior of 120, 40, and 48 participants playing repeatedly. Of the five
benchmarks—the unique (Nash) equilibrium, reinforcement learning, trust-based efficiency, maximum unpredictability, and regret-based
(Impulse Balance) equilibrium—regret for missed opportunities best accounts for the qualitative aspect of participants’ behavior
and regret attenuated by randomization best accounts for the quantitative aspect of behavior. |
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Keywords: | equilibrium impulse balance maximin behavior probability matching reinforcement learning species competition stochastic zero-sum games |
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