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Intensional FOL: Many-Sorted Extension

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arxiv 2409.04469 v1 pith:D354HN4F submitted 2024-09-03 cs.AI

classification cs.AI
keywords ifolmany-sortedintensionalconceptsnaturalapplicationsassociatedattributes
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The concepts used in IFOL have associated to them a list of sorted attributes, and the sorts are the intensional concepts as well. The requirement to extend the unsorted IFOL (Intensional FOL) to many-sorted IFOL is mainly based on the fact that a natural language is implicitly many-sorted and that we intend to use IFOL to support applications that use natural languages. Thus, the proposed version of many-sorted IFOL is just the completion of this conceptual feature of the IFOL.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Neuro-Symbolic Strong-AI Robots with Closed Knowledge Assumption: Learning and Deductions

    cs.LO 2026-02 unverdicted novelty 4.0 of 10

    AGI robots learn and deduce using Belnap's 4-valued bilattice and Closed Knowledge Assumption to expand knowledge while supporting inconsistencies and providing logical security.

  2. Probabilistic Extension of Neuro-Symbolic AGI Robots based on Belnap's Typed Intensional FOL

    cs.AI 2026-07 reject novelty 3.0 of 10

    A theoretical paper defines global and local 'symmetry transformations' to assign probabilities to unknown sentences in a Belnap four-valued intensional logic, with no implementation or validation.

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