Mirror Descent Safe Policy Optimization for Reinforcement Learning Agents

Embodied intelligence and related disciplines have identified several mechanisms that help embodied agents learn how to solve complex problems. Reinforcement learning (RL) is one of the most promising computational approaches toward enhancement of the learning-based problem-solving abilities of such agents. Given the recent rapid evolution of artificial intelligence, RL has become a keystone technology, accelerating scientific discoveries and also finding applications in many other domains. In R