mlsanityData to 7 Oct 2026

First-Order Stable Model Semantics with Intensional Functions

arXiv 2307.10225 ↗First posted 15 Jul 2023cs.AI cs.SCcited by 3

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Abstract (arXiv)

In classical logic, nonBoolean fluents, such as the location of an object, can be naturally described by functions. However, this is not the case in answer set programs, where the values of functions are pre-defined, and nonmonotonicity of the semantics is related to minimizing the extents of predicates but has nothing to do with functions. We extend the first-order stable model semantics by Ferraris, Lee, and Lifschitz to allow intensional functions -- functions that are specified by a logic program just like predicates are specified. We show that many known properties of the stable model semantics are naturally extended to this formalism and compare it with other related approaches to incorporating intensional functions. Furthermore, we use this extension as a basis for defining Answer Set Programming Modulo Theories (ASPMT), analogous to the way that Satisfiability Modulo Theories (SMT) is defined, allowing for SMT-like effective first-order reasoning in the context of ASP. Using SMT solving techniques involving functions, ASPMT can be applied to domains containing real numbers and alleviates the grounding problem. We show that other approaches to integrating ASP and CSP/SMT can be related to special cases of ASPMT in which functions are limited to non-intensional ones.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 4 of its 66 references that are in the map. First posted on arXiv 15 Jul 2023.

Builds on

4 of 66 references.

References · 4

  1. 2016Non-Monotonic Spatial Reasoning with Answer Set Programming Modulo Theoriescited by 6
  2. 2013Satisfiability Modulo ODEscited by 3
  3. 2013A Functional View of Strong Negation in Answer Set Programmingcited by 1
  4. 2017Representing Hybrid Automata by Action Language Modulo Theoriescited by 1

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Citing papers per year: 2024: 2; 2025: 1.

3 papers.