Treffer: On the relation between answer set and SAT procedures (or, between CMODELS and SMODELS)

Title:
On the relation between answer set and SAT procedures (or, between CMODELS and SMODELS)
Source:
Logic programming (21st international conference, ICLP 2005, Sitges, Spain, October 2-5, 2005, proceedings)Lecture notes in computer science. :37-51
Publisher Information:
New York, NY: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 22 ref 1
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
STAR-Lab, DIST, University of Genova, viale Francesco Causa, 13, 16145 Genova, Italy
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17246917
Database:
PASCAL Archive

Weitere Informationen

Answer Set Programming (ASP) is a declarative paradigm for solving search problems. State-of-the-art systems for ASP include SMODELS, DLV, CMODELS, and ASSAT. In this paper, our goal is to study the computational properties of such systems both from a theoretical and an experimental point of view. From the theoretical point of view, we start our analysis with CMODELS and SMODELS. We show that though these two systems are apparently different, they are equivalent on a significant class of programs, called tight. By equivalent, we mean that they explore search trees with the same branching nodes, (assuming, of course, a same branching heuristic). Given our result and that the CMODELS search engine is based on the Davis Logemann Loveland procedure (DLL) for propositional satisfiability (SAT), we are able to establish that many of the properties holding for DLL also hold for CMODELS and thus for SMODELS. On the other hand, we also show that there exist classes of non-tight programs which are exponentially hard for CMODELS, but easy for SMODELS. We also discuss how our results extend to other systems. From the experimental point of view, we analyze which combinations of reasoning strategies work best on which problems. In particular, we extended CMODELS in order to obtain a unique platform with a variety of reasoning strategies, and conducted an extensive experimental analysis on small randomly generated and on large non randomly generated programs. Considering these programs, our results show that the reasoning strategies that work best on the small problems are completely different from the ones that are best on the large ones. These results point out, e.g., that we can hardly expect to develop one solver with the best performances on all the categories of problems. As a consequence, (i) developers should focus on specific classes of benchmarks, and (ii) benchmarking should take into account whether solvers have been designed for specific classes of programs.