Multi-agent Reinforcement Learning

Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) has found many scientific and engineering applications. In this paper, we focus on decentralized MARL policy evaluation with nonlinear function approximation and propose efficient optimization algorithms.
Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu
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Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning