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Searching for Optimization Through Satisfiability: Satisfiability Approaches in Maximum Satisfiability and Ai Planning Zhao Xing
Searching for Optimization Through Satisfiability: Satisfiability Approaches in Maximum Satisfiability and Ai Planning
Zhao Xing
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.
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 30 de mayo de 2010 |
| ISBN13 | 9783838303277 |
| Editores | LAP Lambert Academic Publishing |
| Páginas | 220 |
| Dimensiones | 225 × 12 × 150 mm · 346 g |
| Lengua | Alemán |
Ver todo de Zhao Xing ( Ej. Paperback Book )