Year: 2026
Type: preprint
Abstract: Constraint Answer Set Programming (CASP) is a hybrid paradigm that enriches Answer Set Programming (ASP) with numerical constraint processing, a crucial requirement for many real-world applications. However, the specification of constraints in most CASP solvers aligns more closely with the expressiveness and semantics of the numerical back-end than the ASP paradigm. In the latter, numerical attributes are represented as predicates, which allows declaring default values, leaving the attribute undefined, making non-deterministic assignments with choice rules, or using aggregated values. In CASP, most (if not all) of these features are lost once we switch to a constraint-based representation of those same attributes. In this paper, we present the flingo language (and tool) that incorporates the aforementioned expressiveness within numerical constraints, and we illustrate its use with several examples. Based on previous work that established its semantic foundations, we also present a translation from the newly introduced flingo syntax to regular CASP programs following the clingcon input format.
Source: arXiv (Cornell University)
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7128635614
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