70 citations · 880 across the 62 of their papers we have counts for
4 papers · 1 filter
Deep Primal-Dual Reinforcement Learning: Accelerating Actor-Critic using Bellman Duality
Woon Sang Cho, Mengdi Wang
We develop a parameterized Primal-Dual Learning method based on deep neural networks for Markov decision process with large state space and off-policy reinforcement learning. I…
Primal-Dual Learning: Sample Complexity and Sublinear Run Time for Ergodic Markov Decision Problems
Mengdi Wang
Consider the problem of approximating the optimal policy of a Markov decision process (MDP) by sampling state transitions. In contrast to existing reinforcement learning methods th…
Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes
Aaron Sidford, Mengdi Wang, Xian Wu +1
In this paper we provide faster algorithms for approximately solving discounted Markov Decision Processes in multiple parameter regimes. Given a discounted Markov Decision Process…
Lower Bound On the Computational Complexity of Discounted Markov Decision Problems
Yichen Chen, Mengdi Wang
We study the computational complexity of the infinite-horizon discounted-reward Markov Decision Problem (MDP) with a finite state space and a finite action space $|…