Symmetry breaking in a new stable model search method

17 pages•Published: November 18, 2018

Abstract

In this work, we investigate the inclusion of symmetry breaking in the answer set programming (ASP) framework. The notion of symmetry is widely studied in various domains. Particularly, in the field of constraint programming, where symmetry breaking made a significant improvement in the performances of many constraint solvers. Usually, combinatorial problems contain a lot of symmetries that could render their resolution difficult for the solvers that do not consider them. Indeed, these symmetries guide the solvers in the useless exploration of symmetric and redundant branches of the search tree. The ASP framework is well-known in knowledge representation and reasoning. How- ever, only few works on symmetry in ASP exist. We propose in this paper a new ASP solver based on a novel semantics that we enhance by symmetry breaking. This method with symmetry elimination is implemented and used for the resolution of a large variety of combinatorial problems. The obtained results are very promising and showcase an advantage when using our method in comparison to other known ASP methods.

Keyphrases: Answer Set Programming, logic programming, stable models, symmetry breaking

In: Gilles Barthe, Konstantin Korovin, Stephan Schulz, Martin Suda, Geoff Sutcliffe and Margus Veanes (editors). LPAR-22 Workshop and Short Paper Proceedings, vol 9, pages 58--74

Links:	https://easychair.org/publications/paper/NnGp
	https://doi.org/10.29007/1l5r