• Towards fewer parameters for S...

Treffer: Towards fewer parameters for SAT clause weighting algorithms

Title:
Towards fewer parameters for SAT clause weighting algorithms
Authors:
THORNTON, John, PULLAN, Wayne, TERRY, Justin
Source:
AI 2002 : advances in artificial intelligence (Canberra, 2-6 December 2002)Lecture notes in computer science. :569-578
Publisher Information:
Berlin: Springer, 2002.
Publication Year:
2002
Physical Description:
print, 11 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Apprentissage et systèmes adaptatifs, Learning and adaptive systems, Algorithme compétitif, Competitive algorithms, Logique propositionnelle, Propositional logic, Lógica proposicional, Pondération, Weighting, Ponderación, Problème satisfiabilité, Satisfiability problem, Problema satisfactibilidad, Satisfaction contrainte, Constraint satisfaction, Satisfaccion restricción
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Information Technology, Griffith University Gold Coast, Qld, 4215, Australia
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=14666094
Rights:
Copyright 2003 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.14666094
Database:
PASCAL Archive

Weitere Informationen

Considerable progress has recently been made in using clause weighting algorithms such as DLM and SDF to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this improvement has been bought at the cost of extra parameters and the complexity of fine tuning these parameters to obtain optimal run-time performance. This paper examines the use of parameters, specifically in relation to DLM, to identify underlying features in clause weighting that can be used to eliminate or predict workable parameter settings. To this end we propose and empirically evaluate a simplified clause weighting algorithm that replaces the tabu list and flat moves parameter used in DLM. From this we show that our simplified clause weighting algorithm is competitive with DLM on the four categories of SAT problem for which DLM has already been optimised.