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cs.LG2024
Bisimulation metric for Model Predictive Control
Yutaka Shimizu, Masayoshi Tomizuka
Model-based reinforcement learning has shown promise for improving sample efficiency and decision-making in complex environments. However, existing methods face challenges in train…
cs.LG2024
Strategically Conservative Q-Learning
Yutaka Shimizu, Joey Hong, Sergey Levine +1
Offline reinforcement learning (RL) is a compelling paradigm to extend RL's practical utility by leveraging pre-collected, static datasets, thereby avoiding the limitations associa…