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networked populations

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papersTODAY 04:00 UTC

arXiv paper proposes evolutionary framework for multi-agent Q-learning with mean-field feedback

A new arXiv preprint introduces an evolutionary computation approach to multi-agent reinforcement learning in networked populations. The framework combines individual adaptation, local interactions, and shifting environmental conditions through mean-field environmental feedback. The authors frame the work as a way to study how these coupled learning and environment dynamics interact.

multi-agent/reinforcement-learning/research/evolutionary-computation