Reinforcement learning with restrictions on the action set

Autor:	Bravo, Mario, Faure, Mathieu
Rok vydání:	2013
Předmět:	Computer Science - Computer Science and Game Theory Computer Science - Learning Mathematics - Probability
Druh dokumentu:	Working Paper
Popis:	Consider a 2-player normal-form game repeated over time. We introduce an adaptive learning procedure, where the players only observe their own realized payoff at each stage. We assume that agents do not know their own payoff function, and have no information on the other player. Furthermore, we assume that they have restrictions on their own action set such that, at each stage, their choice is limited to a subset of their action set. We prove that the empirical distributions of play converge to the set of Nash equilibria for zero-sum and potential games, and games where one player has two actions. Comment: 28 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1306.2918 Zobrazit plný text záznamu View this record from Arxiv