A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees

1 code implementation • 31 Jan 2024 • Toshinori Kitamura, Tadashi Kozuno, Masahiro Kato, Yuki Ichihara, Soichiro Nishimori, Akiyoshi Sannai, Sho Sonoda, Wataru Kumagai, Yutaka Matsuo

We study a primal-dual reinforcement learning (RL) algorithm for the online constrained Markov decision processes (CMDP) problem, wherein the agent explores an optimal policy that maximizes return while satisfying constraints.

Reinforcement Learning (RL)