5 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 5 cited
Mastering Strategy Card Game (Legends of Code and Magic) via End-to-End Policy and Optimistic Smooth Fictitious Play
Wei Xi, Yongxin Zhang, Changnan Xiao +5
Deep Reinforcement Learning combined with Fictitious Play shows impressive results on many benchmark games, most of which are, however, single-stage. In contrast, real-world decisi…
cs.LG2021★ 1 cited
An Entropy Regularization Free Mechanism for Policy-based Reinforcement Learning
Changnan Xiao, Haosen Shi, Jiajun Fan +1
Policy-based reinforcement learning methods suffer from the policy collapse problem. We find valued-based reinforcement learning methods with ε-greedy mechanism are capable of enjo…
cs.LG2021
CASA: Bridging the Gap between Policy Improvement and Policy Evaluation with Conflict Averse Policy Iteration
Changnan Xiao, Haosen Shi, Jiajun Fan +2
We study the problem of model-free reinforcement learning, which is often solved following the principle of Generalized Policy Iteration (GPI). While GPI is typically an interplay…