Tag
SafeExplorer introduces an unbiased policy gradient estimator for reinforcement learning with recovery interventions, significantly reducing training-time falls on robot tasks while matching or exceeding standard PPO's final reward.
CAX-Agent is a lightweight agent harness for automating MAPDL finite-element simulations using large language models, with a focus on recovery policies. Evaluation shows model-based recovery achieves best completion rates.