Skip to content
Open access

Bound-Founded Semantics for Answer Set Programming with Difference Constraints: Preliminary Report

Jul 2026 · Electronic Proceedings in Theoretical Computer Science · Vol abs/2607.21201, pp. 360-373 · 0 citations · 17 references
Computer Science

TL;DR

A many-sorted variant of the Bound-founded Logic of Here-and-There (HTb) is introduced, providing a versatile framework capable of characterizing equilibrium models across a wide spectrum of alternative semantics for extensions of ASP with linear constraints.

Abstract

While the integration of linear constraints has significantly expanded the reach of Answer Set Programming (ASP), existing hybrid solvers often rely on disparate semantic underpinnings that lack a unified logical foundation. We address this gap by introducing a many-sorted variant of the Bound-founded Logic of Here-and-There (HTb), providing a versatile framework capable of characterizing equilibrium models across a wide spectrum of alternative semantics for extensions of ASP with linear constraints. We apply this framework to the setting of difference constraints, focusing on the semantic characterization of clingo[DL]. Central to our approach is the formalization of foundedness for numeric variables. By investigating how different hybrid systems - such as clingo[DL], clingcon, and flingo - justify constraint atoms, we uncover the semantic roots of their varying behaviors. This investigation results in a single, consistent framework that not only formalizes the foundations of current systems like clingo[DL] but also facilitates the rigorous study of program simplifications and the future integration of diverse semantic principles.

Read PDF

Similar papers

Aug 2026

Refining Gelfond’s Rationality Principle: Towards More Comprehensive Foundational Principles for Answer Set Semantics

This work proposes to consider the three refined GAS principles as alternative principles for answer set semantics in general and for answer set and world view construction in particular and analyzes the computational complexity of well-supportedness and the rational answer set and world view semantics.

Yi-Dong Shen, Thomas Eiter · 0 citations
Sep 2026

Integration of Minimal Reasons in AMOSUM Constraints

This paper proposes and formalizes two new minimization algorithms that guarantee subset-minimal reasons and ensures cardinality-minimal reasons in the AMOSUM constraint and demonstrates that extending the solver wasp with these minimization strategies leads to substantial performance improvements.

Salvatore Fiorentino · 0 citations

AMO-Aware Optimization in Answer Set Programming ★

This work introduces amomaximize, a novel maximization statement that integrates AMO constraints directly into the objective function, and shows that, in specific scenarios, this approach improves performance compared to clingo.

Mario Alviano, Carmine Dodaro, Salvatore Fiorentino · 0 citations
Preprint Sep 2026

DueList: A Theory of Lists with Combinators for SMT Solvers

This work introduces DueList, an abstraction-refinement approach geared towards list reasoning, which is implemented on top of off-the-shelf SMT solvers and extends reasoning facilities of existing solvers, allowing to conclude about the (un)satisfiability of a larger range of problems, while outperforming existing sol...

Pierre Goutagny, Aymeric Fromherz, Raphaël Monat · 0 citations
Aug 2026

Type-Directed Discretization of Probabilistic Programs

The empirical evaluation shows two complementary strengths of Slice when paired with discrete backends: it enables exact inference for challenging continuous programs that lie beyond the reach of previous exact systems, and is competitive with state-of-the-art exact inference systems for continuous programs.

Katherine Wu, Jules Jacobs, Kevin Batz et al. · 0 citations
Open access Sep 2026

Implementing Metric Temporal Answer Set Programming

This work develops a computational approach to Metric Answer Set Programming to express quantitative temporal constrains, such as durations and deadlines, and effectively decouples metric ASP from the granularity of time, resulting in a solution that is independent of time precision.

Susana Hahn, Arvid Becker, Pedro Cabalar et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.