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Correct-by-Construction Runtime Enforcement in AI -- A Survey
In this paper, we are interested in techniques for constructing runtime enforcers for the concrete application domain of enforcing safety in AI.
Safe Multi-Agent Reinforcement Learning via Shielding
Multi-agent reinforcement learning (MARL) has been increasingly used in a wide range of safety-critical applications, which require guaranteed safety (e. g., no unsafe states are ever visited) during the learning process. Unfortunately, current MARL methods do not have safety guarantees.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
