Using criticalities as a heuristic for answer set programming
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
234 - 246
MetadataShow full item record
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27473
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 (CSMOD-ELS) 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. © Springer-Verlag Berlin Heidelberg 2004.
Showing items related by title, author, creator and subject.
FIR filter design by iterative convex relaxations with rank refinement [Döngüsel kerte aritimli dişbükey gevşetme ile fir süzgeç tasarimi] Dedeoǧlu, M.; Alp, Y.K.; Arikan, O. (IEEE Computer Society, 2014)Finite impulse response (FIR) filters have been a primary topic of digital signal processing since their inception. Although FIR filter design is an old problem, with the developments of fast convex solvers, convex modelling ...
Oguz O. (2010)We present new valid inequalities for 0-1 programming problems that work in similar ways to well known cover inequalities. Discussion and analysis of these cuts is followed by their revision and use in integer programming ...
Lower hedging of American contingent claims with minimal surplus risk in finite-state financial markets by mixed-integer linear programming Pinar, M.Ç. (2014)The lower hedging problem with a minimal expected surplus risk criterion in incomplete markets is studied for American claims in finite state financial markets. It is shown that the lower hedging problem with linear expected ...