A Preliminary Report on Integrating of Answer Set and Constraint Solving

Abstract. Despite all efforts on intelligent grounding, state-of-the-art answer set solvers still have huge memory requirements, because they compute the ground instantiation of the input program before the actual reasoning starts. This prevents ASP to be effective on several classes of problems. In this paper we integrate answer set generation and constraint solving to reduce the memory requirements for a class of multi-sorted logic programs with cardinality constraints. We prove some theoretical results, introduce a provably sound and complete algorithm, and report experimental results showing that our approach can solve problem instances with significantly larger domains.