AI RESEARCH
Randomness is sometimes necessary for coordination
arXiv CS.AI
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ArXi:2605.06825v1 Announce Type: new Full parameter sharing is standard in cooperative multi-agent reinforcement learning (MARL) for homogeneous agents. Under permutation-symmetric observations, however, a shared deterministic policy outputs identical action distributions for every agent, making role differentiation impossible. This failure can theoretically be resolved using symmetry breaking among anonymous identical processors, which requires randomness.