English

Quantification and Aggregation over Concepts of the Ontology

Logic in Computer Science 2023-08-31 v4 Artificial Intelligence

Abstract

We argue that in some KR applications, we want to quantify over sets of concepts formally represented by symbols in the vocabulary. We show that this quantification should be distinguished from second-order quantification and meta-programming quantification. We also investigate the relationship with concepts in intensional logic. We present an extension of first-order logic to support such abstractions, and show that it allows writing expressions of knowledge that are elaboration tolerant. To avoid nonsensical sentences in this formalism, we refine the concept of well-formed sentences, and propose a method to verify well-formedness with a complexity that is linear with the number of tokens in the formula. We have extended FO(.), a Knowledge Representation language, and IDP-Z3, a reasoning engine for FO(.), accordingly. We show that this extension was essential in accurately modelling various problem domains in an elaboration-tolerant way, i.e., without reification.

Keywords

Cite

@article{arxiv.2202.00898,
  title  = {Quantification and Aggregation over Concepts of the Ontology},
  author = {Pierre Carbonnelle and Matthias Van der Hallen and Marc Denecker},
  journal= {arXiv preprint arXiv:2202.00898},
  year   = {2023}
}

Comments

In Proceedings ICLP 2023, arXiv:2308.14898

R2 v1 2026-06-24T09:15:13.938Z