3 papers
math.OC2026
On the Policy Convergence of Policy Mirror Descent Methods
Wenye Li, Ke Wei
We study the policy convergence of unregularized policy mirror descent (PMD) with arbitrary constant step sizes for finite discounted Markov decision processes. We focus on decompo…
math.OC2025
Policy Mirror Descent with Temporal Difference Learning: Sample Complexity under Online Markov Data
Wenye Li, Hongxu Chen, Jiacai Liu +1
This paper studies the policy mirror descent (PMD) method, which is a general policy optimization framework in reinforcement learning and can cover a wide range of policy gradient…
math.OC2025
On the Convergence of Policy Mirror Descent with Temporal Difference Evaluation
Jiacai Liu, Wenye Li, Ke Wei
Policy mirror descent (PMD) is a general policy optimization framework in reinforcement learning, which can cover a wide range of typical policy optimization methods by specifying…