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Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models

作者：作者信息待提取 · 单位：New York University, Brown University, University of Toronto, Meta – FAIR · 来源：General Approaches to World Models · 发布日期：2025 · 分类：8. World Models in the context of Model-Based RL

潜空间世界模型基于模型的强化学习
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Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models figure
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