This AI Paper Introduces the Diffusion World Model (DWM): A General Framework for Leveraging Diffusion Models as World Models in the Context of Offline Reinforcement learning

Reinforcement learning (RL) comprises a wide range of algorithms, typically divided into two main groups: model-based (MB) and model-free (MF) methods. MB algorithms rely on predictive models of environment feedback, termed world models, which simulate real-world dynamics. These models facilitate policy derivation through action exploration or policy optimization. Despite their potential, MB methods often need […]

The post This AI Paper Introduces the Diffusion World Model (DWM): A General Framework for Leveraging Diffusion Models as World Models in the Context …

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