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WHALE: Towards Generalizable and Scalable World Models for Embodied Decision-making
Zhilong Zhang, Ruifeng Chen, Junyin Ye +8
World models play a crucial role in decision-making within embodied environments, enabling cost-free explorations that would otherwise be expensive in the real world. To facilitate…
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
Tian Xu, Zhilong Zhang, Ruishuo Chen +2
As a prominent category of imitation learning methods, adversarial imitation learning (AIL) has garnered significant practical success powered by neural network approximation. Howe…
BWArea Model: Learning World Model, Inverse Dynamics, and Policy for Controllable Language Generation
Chengxing Jia, Pengyuan Wang, Ziniu Li +4
Large language models (LLMs) have catalyzed a paradigm shift in natural language processing, yet their limited controllability poses a significant challenge for downstream applicat…
Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning
Haoxin Lin, Yu-Yan Xu, Yihao Sun +6
Model-based methods in reinforcement learning offer a promising approach to enhance data efficiency by facilitating policy exploration within a dynamics model. However, accurately…