Distributed Neural Policy Gradient Algorithm for Global Convergence of Networked Multiagent Reinforcement Learning

This article studies the networked multiagent reinforcement learning problem, where the objective of agents is to collaboratively maximize the discounted average cumulative rewards. Different from the existing methods that suffer from poor expression due to linear function approximation, we propose...

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