5 citations · 16 across the 8 of their papers we have counts for
4 papers · 1 filter
A Review for Deep Reinforcement Learning in Atari:Benchmarks, Challenges, and Solutions
Jiajun Fan
The Arcade Learning Environment (ALE) is proposed as an evaluation platform for empirically assessing the generality of agents across dozens of Atari 2600 games. ALE offers various…
GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
Jiajun Fan, Changnan Xiao, Yue Huang
Deep Q Network (DQN) firstly kicked the door of deep reinforcement learning (DRL) via combining deep learning (DL) with reinforcement learning (RL), which has noticed that the dist…
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…
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…