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Adaptive Learning In Finitely Repeated Games, Naoki Funai

Naoki Funai

This paper investigates the way in which adaptive players behave in the long-run in finitely repeated games. Each player assigns subjective payoff assessments to his own actions and chooses the action which has the highest assessment at each of his information sets. After receiving payoffs, players update their own assessments of chosen actions using the realized payoffs in an adaptive manner; we consider the updating rules of Watkins and Dayan (1992) and Sarin and Vahid (1999). When players experience random shocks on their assessments, players' behavior strategies converge to a unique agent quantal response equilibrium (McKelvey and Palfrey, 1998) if …