Hierarchical Planning with Latent World Models
World models are a promising path to zero-shot embodied control through planning. However, existing world model planners struggle on long-horizon, multi-stage tasks: prediction errors compound and naive search is exponential in the planning horizon. Hierarchy mitigates both by decomposing tasks into shorter, tractable subproblems; yet prior hierarchical approaches either amortize control into task-specific policies (hierarchical RL) or assume low-dimensional states and known dynamics (classical hierarchical MPC). We present Hierarchical Planning with Latent World Models (HWM), an architecture and planning paradigm for hierarchical model predictive control directly on visual world models t...
| Authors | Wancong Zhang, Basile Terver, Artem Zholus et al. |
|---|---|
| Primary category | cs.LG |
| Published | 3 April 2026 |
| Last updated at source | 12 October 2026 |
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