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VOiLA: Vectorized Online Planning with Learned Diffusion Models for POMDP Agents
Planning under uncertainty is an essential capability for autonomous robots. The Partially Observable Markov Decision Process (POMDP) provides a powerful framework for such a capability. Although POMDP-based planning has advanced significantly, its application to real-world problems is often limited
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