AN OPERANT APPROACH TO THE ITERATED PRISONERS' DILEMMA: EMERGENCE OF STABLE COOPERATION AFTER INDIRECT REINFORCEMENT OF CONTROLLlNG BEHAVIORS IN ARTIFICIAL LEARNING AGENTS

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JÉRÉMIE JOZEFOWIEZ
JEAN-CLAUDE DARCHEVILLE
PHILlPPE PREUX

Abstract

We propose an operant approach to the emergence of cooperation in the iterated Prisoners' Oilemma (IPO). The approach yields to the design of reinforcementlearning agents whose behavioral repertoire includes not only cooperation-related behaviors, but also controlling behaviors that may influence the behavior of the other player. The task of an agent is to learn to coordinate its own cooperation- and controlrelated behaviors with those of the other agents. It is suggested that this situation is closer to natural cooperative situations than the classical approaches to the IPO.

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How to Cite
JOZEFOWIEZ, J., DARCHEVILLE, J.-C., & PREUX, P. (2011). AN OPERANT APPROACH TO THE ITERATED PRISONERS’ DILEMMA: EMERGENCE OF STABLE COOPERATION AFTER INDIRECT REINFORCEMENT OF CONTROLLlNG BEHAVIORS IN ARTIFICIAL LEARNING AGENTS. Mexican Journal of Behavior Analysis, 26(2), 211–227. https://doi.org/10.5514/rmac.v26.i2.25155