1 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2025
Policy Constraint by Only Support Constraint for Offline Reinforcement Learning
Yunkai Gao, Jiaming Guo, Fan Wu +1
Offline reinforcement learning (RL) aims to optimize a policy by using pre-collected datasets, to maximize cumulative rewards. However, offline reinforcement learning suffers chall…
cs.LG2023★ 1 cited
Context Shift Reduction for Offline Meta-Reinforcement Learning
Yunkai Gao, Rui Zhang, Jiaming Guo +10
Offline meta-reinforcement learning (OMRL) utilizes pre-collected offline datasets to enhance the agent's generalization ability on unseen tasks. However, the context shift problem…
cs.LG2023★ 1 cited
Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
Siming Lan, Rui Zhang, Qi Yi +10
In the field of multi-task reinforcement learning, the modular principle, which involves specializing functionalities into different modules and combining them appropriately, has b…