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cs.RO2023
Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration
Jinning Li, Xinyi Liu, Banghua Zhu +4
Safe Reinforcement Learning (RL) aims to find a policy that achieves high rewards while satisfying cost constraints. When learning from scratch, safe RL agents tend to be overly co…
cs.MA2023
Quantifying Agent Interaction in Multi-agent Reinforcement Learning for Cost-efficient Generalization
Yuxin Chen, Chen Tang, Ran Tian +4
Generalization poses a significant challenge in Multi-agent Reinforcement Learning (MARL). The extent to which an agent is influenced by unseen co-players depends on the agent's po…