InfoCon: Concept Discovery with Generative and Discriminative Informativeness

arXiv:2404.10606v1 Announce Type: cross
Abstract: We focus on the self-supervised discovery of manipulation concepts that can be adapted and reassembled to address various robotic tasks. We propose that the decision to conceptualize a physical procedure should not depend on how we name it (semantics) but rather on the significance of the informativeness in its representation regarding the low-level physical state and state changes. We model manipulation concepts (discrete symbols) as generative and discriminative goals and derive metrics that can autonomously …

abstract arxiv concept concepts cs.ai cs.lg cs.ro decision discovery focus generative manipulation robotic semantics significance tasks type