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SafeDiSTL: Decomposing Joint Constraints for Safe Multi-Agent Reinforcement Learning

Zheng, Hongrui et al.
arXiv (All) · Papers
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Cooperative multi-agent tasks often impose constraints on a shared objective or collective safety. A team level violation cost function can measure this constraint outcome, but does not distinguish which agents' actions most strongly influence that violation. We present SafeDiSTL, a constrained mult
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