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# Hierarchical Control

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  1. bioRxiv

    Why place cells fire in many fields across large spaces: a hierarchical predictive map ties field statistics to the scale of behavior

    In large environments at naturalistic scale, rat and bat hippocampal CA1 place cells often carry multiple irregularly spaced firing fields, whereas the classical single-scale successor representation holds only in small enclosures. The factorised hierarchical successor representation (fHSR) folds one-step actions together with subgoal-directed subroutines into a predictive map, then decomposes the maps of several tasks into a non-negative overcomplete basis that gives each model cell its tuning. On a 48 m rat track and a 200 m bat track the model reproduced the gamma-Poisson overdispersion of field counts, and it predicted a spatial periodicity of population activity whose wavelength is independent of track length, a prediction tested in rat data.

  2. arXiv

    Distilling a single-agent carrying policy into a reusable low-level skill lets a high-level policy coordinate humanoids for sofa carrying, sofa pushing, and four-agent transport

    The work proposes a hierarchical framework that relabels successful rollouts of a single-agent physics-based human-object interaction teacher as short-horizon object-proxy displacement supervision, distilling a frozen reusable Object-oriented Motion Skill, while downstream training only learns a high-level policy that emits region-wise proxy-motion commands; in Isaac Gym with 4096 parallel environments the skill achieves better tracking than InterPhys and SkillMimic on both teacher-rollout and random proxy-motion targets, and supports two-human sofa carrying, four-human H-box and cross-box carrying, and two- and four-human sofa pushing.

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