Abduction Without a Body? Representational Grounding and the Abduction Loop for Scientific Hypothesis Generation

Noosaga Placements

• Artificial Intelligencesubfield90%
  The paper addresses a core AI question about the necessity of embodiment for scientific abduction, proposing an architecture for hypothesis generation and a benchmark for evaluation.
  Can scientific abduction occur without continuous sensorimotor embodiment?We operationalize the mechanism as a practical architecture, the Abduction Loopthe DAB-30 benchmark
• Foundation Modelsframework80%
  The motivating case uses a multimodal LLM (Claude Fable 5) to generate and verify an identity hypothesis, and the architecture includes a vision-language component for motif extraction.
  a multimodal model, given a figure of a gravitational-memory transport model, generated and then verified the hypothesisA vision–language component segments each view into motifs
• Knowledge Representation Reasoningsubfield70%
  The paper discusses representational grounding, the role of representations in exposing structural invariants, and the use of conventions as a canonicalization layer, which are central to knowledge representation and reasoning.
  representational grounding is the acquisition of new inferential affordances through transformations into representations whose structural organization exposes latent invariantsconvention space is the space of graphical motif classes produced by independently evolved scientific drawing conventions that preserve common structural invariants
• Vision-Language Modelsframework70%
  The motivating case involves a multimodal model processing a figure, and the architecture includes a vision-language component for motif extraction.
  a multimodal model, given a figure of a gravitational-memory transport modelA vision–language component segments each view into motifs
• Computer Visionsubfield60%
  The architecture includes motif extraction from diagrams and uses multimodal models, which involve computer vision techniques for visual understanding.
  A vision–language component segments each view into motifs and extracts their structural contenta multimodal model, given a figure of a gravitational-memory transport model
• Information Retrievalsubfield60%
  The paper addresses a cross-domain retrieval problem where fields share no discriminating vocabulary, proposing convention space as a retrieval mechanism.
  convention space ... yields a concrete answer to a hard retrieval problem: how to find mathematically related work when two fields share no discriminating vocabularyretrieval in convention space yields higher precision for crossdomain structural correspondences than retrieval based on lexical similarity

Abstract

Can scientific abduction occur without continuous sensorimotor embodiment? Recent arguments in AI and philosophy of science hold that genuine hypothesis generation requires an agent continuously coupled to the physical world. We defend a narrower claim: online embodiment is not necessary for every abductive scientific act. Our focus is identity abduction: the inference that two independently developed structures are one object under an explicit correspondence, reached through representational grounding rather than bodily interaction. An agent may acquire new inferential affordances not through physical interaction but through transformations into representations that expose latent invariants. Scientific diagrams are a practical substrate because they embody independently evolved conventions that partially canonicalize symmetry, topology, and operator structure across disciplines - a property we develop as convention space, which answers a hard retrieval problem: finding mathematically related work when two fields share no discriminating vocabulary. We operationalize the mechanism as an architecture, the Abduction Loop: representation generation, motif extraction, convention-space canonicalization, cross-domain retrieval, identity-hypothesis generation, and adversarial verification, with abstention as the designed default. A documented episode, in which a multimodal model given a figure of a gravitational-memory transport model generated and then verified the hypothesis that its central differential complex is equivalent to the spherical Kaiser-Squires mass-mapping complex of weak-lensing cosmology, serves as a motivating possibility witness from which the architecture is abstracted, not as evidence of general capability. We close with a falsifiable evaluation program, the DAB-30 benchmark. The contribution is a mechanistic proposal, an architecture, and a test program.

Paper Context