7 citations · 32 across the 33 of their papers we have counts for
5 papers · 1 filter
RPM: Generalizable Behaviors for Multi-Agent Reinforcement Learning
Wei Qiu, Xiao Ma, Bo An +3
Despite the recent advancement in multi-agent reinforcement learning (MARL), the MARL agents easily overfit the training environment and perform poorly in the evaluation scenarios…
Boosting Offline Reinforcement Learning via Data Rebalancing
Yang Yue, Bingyi Kang, Xiao Ma +3
Offline reinforcement learning (RL) is challenged by the distributional shift between learning policies and datasets. To address this problem, existing works mainly focus on design…
Mutual Information Regularized Offline Reinforcement Learning
Xiao Ma, Bingyi Kang, Zhongwen Xu +2
The major challenge of offline RL is the distribution shift that appears when out-of-distribution actions are queried, which makes the policy improvement direction biased by extrap…
Imitation Learning via Differentiable Physics
Siwei Chen, Xiao Ma, Zhongwen Xu
Existing imitation learning (IL) methods such as inverse reinforcement learning (IRL) usually have a double-loop training process, alternating between learning a reward function an…
Hierarchical Reinforcement Learning under Mixed Observability
Hai Nguyen, Zhihan Yang, Andrea Baisero +3
The framework of mixed observable Markov decision processes (MOMDP) models many robotic domains in which some state variables are fully observable while others are not. In this wor…