3 papers
cs.LG2026
Role-Adaptive Policy Optimization for Offline Reinforcement Learning
Seonvin Cho, Soohyun Choi, Songnam Hong
Policy regularization in offline reinforcement learning balances policy improvement against reliance on uncertain value estimates. This balance can differ between selecting actions…
cs.LG2026
Is One Step Enough for Offline Policy Improvement?
Soohyun Choi, Seonvin Cho, Songnam Hong
Behavior regularization in offline reinforcement learning limits the exploitation of critic errors, but strong anchoring can also restrict policy improvement. We study how policy i…
cs.LG2026
PathBridger: Subgoal Bridges for Offline Goal-Conditioned Reinforcement Learning
Soohyun Choi, Seonvin Cho, Songnam Hong
Offline goal-conditioned reinforcement learning (GCRL) aims to learn policies for reaching diverse goals entirely from fixed trajectory data. Long-horizon offline GCRL remains chal…