3 papers
cs.LG2026
Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark
Yang Fu, Haomin Bao, Rohit Sonker +4
Offline reinforcement learning (RL) offers a promising route for developing plasma controllers from historical tokamak data, since online trial-and-error on real devices is costly…
cs.LG2026
Occupancy Reward Shaping: Improving Credit Assignment for Offline Goal-Conditioned Reinforcement Learning
Aravind Venugopal, Jiayu Chen, Xudong Wu +3
The temporal lag between actions and their long-term consequences makes credit assignment a challenge when learning goal-directed behaviors from data. Generative world models captu…
cs.LG2026
Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning
Jiayu Chen, Le Xu, Aravind Venugopal +1
Offline reinforcement learning (RL) offers a powerful paradigm for data-driven control. Compared to model-free approaches, offline model-based RL (MBRL) explicitly learns a world m…