Safe Exploration Method for Reinforcement Learning under Existence of Disturbance

1 code implementation • 30 Sep 2022 • Yoshihiro Okawa, Tomotake Sasaki, Hitoshi Yanami, Toru Namerikawa

We define the safety during learning as satisfaction of the constraint conditions explicitly defined in terms of the state and propose a safe exploration method that uses partial prior knowledge of a controlled object and disturbance.

reinforcement-learning Reinforcement Learning (RL) +1