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Abstract answer set solvers with backjumping and learning

Published online by Cambridge University Press:  22 February 2011

YULIYA LIERLER
YULIYA LIERLER*
Affiliation:
Department of Computer Science, University of Kentucky, 773C Anderson Hall, Lexington, USA (e-mail: yuliya@cs.uky.edu)
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Abstract

Nieuwenhuis et al. (2006. Solving SAT and SAT modulo theories: From an abstract Davis-Putnam-Logemann-Loveland procedure to DPLL(T). Journal of the ACM 53(6), 937977 showed how to describe enhancements of the Davis–Putnam–Logemann–Loveland algorithm using transition systems, instead of pseudocode. We design a similar framework for several algorithms that generate answer sets for logic programs: smodels, smodelscc, asp-sat with Learning (cmodels), and a newly designed and implemented algorithm sup. This approach to describe answer set solvers makes it easier to prove their correctness, to compare them, and to design new systems.

Keywords

answer set programminginferencelearning
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 11 , Special Issue 2-3: The 24th International Conference on Logic Programming (ICLP 2008) , March 2011 , pp. 135 - 169
Copyright
Copyright © Cambridge University Press 2011

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