Gradient descent for symmetric and asymmetric multiagent reinforcement learning

Abstract

A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the problem with agents involved in the learning task having equal information states. Respectively, in asymmetric multiagent reinforcement learning, the information states are not… (More)

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