Learning Decision Criteria from Play

Titelangaben

Galeazzi, Paolo ; Madsen, Mathias W.:
Learning Decision Criteria from Play.
In: Dynamic Games and Applications. (2024) .
ISSN 2153-0793
DOI der Verlagsversion: https://doi.org/10.1007/s13235-024-00595-2

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Abstract

This paper investigates population games under ambiguity in which players may adopt decision criteria different from one another. After defining equilibria for these situations by extending well-known decision-theoretic criteria to the game-theoretic context, we apply these concepts to examine the case of two-person games played within a population whose relative proportions of decision criteria are unknown to the players. We state necessary and sufficient conditions under which such games prompt the players to reveal their decision criterion through their actions, and we show when the relative proportions may be learned by observing the increasingly informed agents play.