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Distributed scalable coupled policy algorithm for networked multi-agent reinforcement learning

Dai, Pengcheng et al.
arXiv (All) · Papers
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multiagent-systems
This paper studies networked multi-agent reinforcement learning (NMARL) with interdependent rewards and coupled policies. In this setting, each agent's reward depends on its own state-action pair as well as those of its direct neighbors, and each agent's policy is parameterized by its local paramete
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