Tianli Ma

Safe Reinforcement Learning by Imagining the Near Future

2022 · arXiv (Cornell University)

Safe reinforcement learning is a promising path toward applying reinforcement learning algorithms to real-world problems, where suboptimal behaviors may lead to actual negative consequences. In this work, we focus on the setting where unsafe states …