Using criticalities as a heuristic for answer set programming

In Vladimir Lifschitz & Ilkka Niemela (eds.), Logic Programming and Nonmonotonic Reasoning, Lecture Notes in Artificial Intelligence 2923 (7th International Conference, LPNMR 2004, Fort Lauderdale, FL, January 6-8, 2004 Proceedings). Berlin, Heidelberg: Springer. pp. 234-246 (2003)
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Answer Set Programming is a new paradigm based on logic programming. The main component of answer set programming is a system that finds the answer sets of logic programs. During the computation of an answer set, systems are faced with choice points where they have to select a literal and assign it a truth value. Generally, systems utilize some heuristics to choose new literals at the choice points. The heuristic used is one of the key factors for the performance of the system. A new heuristic for answer set programming has been developed. This heuristic is inspired by hierarchical planning. The notion of criticality, which was introduced for generating abstraction hierarchies in hierarchical planning, is used in this heuristic. The resulting system (CSMODELS) uses this new heuristic in a static way. CSMODELS is based on the system SMODELS. The experimental results show that this new heuristic is promising for answer set programming. A comparison of search times with SMODELS demonstrate CSMODELS’ usefulness.

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Varol Akman
Bilkent University

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Automatically generating abstractions for planning.Craig A. Knoblock - 1994 - Artificial Intelligence 68 (2):243-302.
Calculating criticalities.A. Bundy, F. Giunchiglia, R. Sebastiani & T. Walsh - 1996 - Artificial Intelligence 88 (1-2):39-67.

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