most citedLower Bound On the Computational Complexity of Discounted Markov Decision Problems

11 citations · 11 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2018

Scalable Bilinear Learning Using State and Action Features

Yichen Chen, Lihong Li, Mengdi Wang

Approximate linear programming (ALP) represents one of the major algorithmic families to solve large-scale Markov decision processes (MDP). In this work, we study a primal-dual for…

cs.CC2017★ 11 cited

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 $|…