Searching for Optimization through Satisfiability: Satisfiability Approaches in Maximum Satisfiability and AI Planning - Couverture souple

Xing, Zhao

 
9783838303277: Searching for Optimization through Satisfiability: Satisfiability Approaches in Maximum Satisfiability and AI Planning
Couverture souple
ISBN 10 : 383830327X ISBN 13 : 9783838303277
Editeur : LAP LAMBERT Academic Publishing, 2010

Synopsis

This book studies two optimization problems, maximum satisfiability and planing of satisfiability. The maximum satisfiability problem (max-SAT) is the optimization counterpart of the satisfiability problem (SAT). The goal of max-SAT is to maximize the number of clauses satisfied. planning as satisfiability is a class of planning aiming to achieve a plan with optimal resource, cost, or makespan by using the SAT approach. We present a mix- SAT formulation for these two optimization problems and examine to extend the Davis-Putnam-Logemann- Loveland (DPLL) procedure, which is the basic framework for the original SAT problem, for this mix- SAT formulation. We progressively develop a series of algorithms and reconsider many general SAT techniques for these two optimization problems.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book studies two optimization problems, maximum satisfiability and planing of satisfiability. The maximum satisfiability problem (max-SAT) is the optimization counterpart of the satisfiability problem (SAT). The goal of max-SAT is to maximize the number of clauses satisfied. planning as satisfiability is a class of planning aiming to achieve a plan with optimal resource, cost, or makespan by using the SAT approach. We present a mix- SAT formulation for these two optimization problems and examine to extend the Davis-Putnam-Logemann- Loveland (DPLL) procedure, which is the basic framework for the original SAT problem, for this mix- SAT formulation. We progressively develop a series of algorithms and reconsider many general SAT techniques for these two optimization problems.

Biographie de l'auteur

Dr. Xing received his Ph.D. degree from Washington University in St. Louis in 2008. His research interests include heuristic search, SAT, and AI planning. He is the author of more than 15 refereed publications, and a winner of International Planning Competitions. In his spare time, Dr. Xing likes swimming, history, and value investing.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2010
Langue
anglais
ISBN 10 
383830327X
ISBN 13 
9783838303277
Reliure
Broché
Nombre de pages
220
Coordonnées du fabricant
non disponible
Personne responsable
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