Translation-based Constraint Answer Set Solving

TL;DR

This paper presents a novel method for solving constraint satisfaction problems by translating them into answer set programming, leveraging ASP's unit-propagation to achieve local consistency properties and improve computational efficiency.

Contribution

The paper introduces a translation-based approach that enables ASP solvers to perform local consistency enforcement for constraint satisfaction problems, enhancing solving capabilities.

Findings

ASP-based reformulations achieve arc, bound, and range consistency.

Experiments show improved computational performance.

Method effectively integrates constraint satisfaction with ASP.

Abstract

We solve constraint satisfaction problems through translation to answer set programming (ASP). Our reformulations have the property that unit-propagation in the ASP solver achieves well defined local consistency properties like arc, bound and range consistency. Experiments demonstrate the computational value of this approach.