Safe Reinforcement Learning
Balancing Performance and Safety in RL Safe Reinforcement Learning (RL) is a subset of RL that focuses on learning policies that not only maximize the long-term reward but also ensure reasonable system performance and/or respect safety constraints during the learning and/or deployment processes [1]. Safety is the opposite of risk, which refers to the stochastic nature of the environment. An optimal policy for long-term reward maximization may still perform poorly in some catastrophic situations due to inherent uncertainty....