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Mean and variance responsive learning

Carlos Oyarzun and Rajiv Sarin

Games and Economic Behavior, 2012, vol. 75, issue 2, 855-866

Abstract: Decision makers are often described as seeking higher expected payoffs and avoiding higher variance in payoffs. We provide some necessary and some sufficient conditions for learning rules, that assume the agent has little prior and feedback information about the environment, to reflect such preferences. We adopt the framework of Börgers, Morales and Sarin (2004, Econometrica) who provide similar results for learning rules that seek higher expected payoffs. Our analysis reveals that a concern for variance leads to quadratic transformations of payoffs to appear in the learning rule.

Keywords: Learning; Reinforcement learning; Mean and variance preferences (search for similar items in EconPapers)
JEL-codes: D81 D83 (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:eee:gamebe:v:75:y:2012:i:2:p:855-866

DOI: 10.1016/j.geb.2012.02.013

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