Decentralized Safe Multi-Agent Reinforcement Learning via Predictive Shielding
A decentralized framework that integrates predictive shielding with model-based finite horizon Q-learning is proposed, which allows agents to safely adapt their pre-trained policies during deployment and introduces a communication- free protocol for conflict resolution.
Y. El Yamani, Hanna Krasowski, Elena Vanneaux
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