AINeutralarXiv – CS AI · Mar 57/10
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Learning Approximate Nash Equilibria in Cooperative Multi-Agent Reinforcement Learning via Mean-Field Subsampling
Researchers propose ALTERNATING-MARL, a new framework for cooperative multi-agent reinforcement learning that enables a global agent to learn with massive populations under communication constraints. The method achieves approximate Nash equilibrium convergence while only observing a subset of local agent states, with applications in multi-robot control and federated optimization.
$MKR