Abstract
Answer Set Programming (ASP) and propositional satisfiability (SAT) are closely related. In some recent work we have shown that, on a wide set of logic programs called “tight”, the main search procedures used by ASP and SAT systems are equivalent, i.e., that they explore search trees with the same branching nodes. In this paper, we focus on the experimental evaluation of different search strategies, heuristics and their combinations that have been shown to be effective in the SAT community, in ASP systems. Our results show that, despite the strong link between ASP and SAT, it is not always the case that search strategies, heuristics and/or their combinations that currently dominate in SAT are also bound to dominate in ASP. We provide a detailed experimental evaluation for this phenomenon and we shed light on future development of efficient Answer Set solvers.
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Giunchiglia, E., Maratea, M. (2005). Evaluating Search Strategies and Heuristics for Efficient Answer Set Programming. In: Bandini, S., Manzoni, S. (eds) AI*IA 2005: Advances in Artificial Intelligence. AI*IA 2005. Lecture Notes in Computer Science(), vol 3673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558590_13
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DOI: https://doi.org/10.1007/11558590_13
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