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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.
| Autorius: | Zhao Xing |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2010 |
| Knygos puslapių skaičius: | 220 |
| ISBN-10: | 383830327X |
| ISBN-13: | 9783838303277 |
| Formatas: | 220 x 150 x 14 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Searching for Optimization through Satisfiability: Satisfiability Approaches in Maximum Satisfiability and AI Planning“
