2 papers
cs.LG2026
Boundary-Seeking Policy Gradient for Safe Reinforcement Learning
Chenhua Fan, Jiahui Zhu, Yuhang Zhang +1
Safe reinforcement learning maximizes reward subject to safety constraints. For Constrained Markov Decision Processes, the linear-programming view over occupancy measures implies t…
cs.LG2021
Steadily Learn to Drive with Virtual Memory
Yuhang Zhang, Yao Mu, Yujie Yang +4
Reinforcement learning has shown great potential in developing high-level autonomous driving. However, for high-dimensional tasks, current RL methods suffer from low data efficienc…