Reference points and learning

نویسندگان

چکیده

This paper studies learning when agents evaluate outcomes in comparison to reference points, which may be adjusted light of experience. It shows that certain models reinforcement learning, motivated by those popular machine and neuroscience, lead classes recursive preferences.

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This note provides a positive answer to the following question. Is it possible to define a set of preference relations, one for each node of a decision tree, such that these preferences satisfy the reduction of compound lotteries axiom and dynamic consistency, and yet do not converge to expected utility? It is argued that updated preferences necessarily have one affine indifference curve but th...

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ژورنال

عنوان ژورنال: Journal of Mathematical Economics

سال: 2022

ISSN: ['1873-1538', '0304-4068']

DOI: https://doi.org/10.1016/j.jmateco.2021.102621