2 papers
cs.LG2025
Achieving Instance-dependent Sample Complexity for Constrained Markov Decision Process
Jiashuo Jiang, Yinyu Ye
We consider the reinforcement learning problem for the constrained Markov decision process (CMDP), which plays a central role in satisfying safety or resource constraints in sequen…
cs.LG2025
Adaptive Resolving Methods for Reinforcement Learning with Function Approximations
Jiashuo Jiang, Yiming Zong, Yinyu Ye
Reinforcement learning (RL) problems are fundamental in online decision-making and have been instrumental in finding an optimal policy for Markov decision processes (MDPs). Functio…