Safe Meta-Reinforcement Learning via Information Space Reachability
This paper proposes a safe meta-RL framework that explicitly accounts for safety during adaptation, and develops a safe meta-RL algorithm that learns the safety value function and leverages it for safety filtering and constrained policy optimization.
Ze-Yang Li, Sunbochen Tang, Navid Azizan
· 0 citations