WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning

Safe exploration is regarded as a key priority area for reinforcement learning research. With separate reward and safety signals, it is natural to cast it as constrained reinforcement learning, where expected long-term costs of policies are constrained. However, it can be hazardous to set constraints on the expected safety signal without...

Back to the Future: Solving Hidden Parameter MDPs with Hindsight

CEM: Constrained Entropy Maximization for Task-Agnostic Safe Exploration

Without an assigned task, a suitable intrinsic objective for an agent is to explore the environment efficiently. However, the pursuit of exploration will inevitably bring more safety risks.<br/>An under-explored aspect of reinforcement learning is how to achieve safe efficient exploration when the task is unknown.<br/>In this paper, we propose a...