New Developments in Symmetry Breaking in Search Using Computational Group Theory

摘要

Symmetry-breaking in constraint satisfaction problems is a well-established area of AI research which has recently developed strong interactions with symbolic computation, in the form of computational group theory. GE-trees are a new conceptual abstraction, providing low-degree polynomial time methods for breaking value symmetries in constraint satisfication problems. In this paper we analyse the structure of symmetry groups of constraint satisfaction problems, and implement several combinations of GE-trees and the classical SBDD method for breaking all symmetries. We prove the efficacy of our techniques, and present preliminary experimental evidence of their practical efficiency.