Learning to Collude : A Partial Folk Theorem for Smooth Fictitious Play

We propose an extension to smooth fictitious play and prove that play converges to an ε-Markov perfect equilibrium with probability one in a class of stochastic games known as Markov potential games. We then prove a partial Folk theorem for repeated games under one-period perfect monitoring. We show that through repeated interactions, decentralized learning algorithms can learn to both define the terms of a collusive arrangement and to implement that arrangement

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Year of publication:	2022
Authors:	Cartea, Álvaro ; Chang, Patrick ; Penalva, José ; Waldon, Harrison
Publisher:	[S.l.] : SSRN
Subject:	Lernprozess \| Learning process \| Folk-Theorem \| Folk theorem \| Wiederholte Spiele \| Repeated games \| Spieltheorie \| Game theory

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