Collaborative Multi-Agent Reinforcement Learning for Complex Task Solving

This work introduces a novel collaborative multi-agent reinforcement learning framework designed for complex task environments. The approach leverages emergent communication protocols and adaptive role assignment mechanisms to enable efficient agent coordination and task decomposition.

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