The Satisfiability Problem

The Satisfiability Problem

Author: Schöning, Uwe

Publisher: Lehmanns Media

Published: 2013-01-01

Total Pages: 184

ISBN-13: 3865416489

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The satisfiability problem of propositional logic, SAT for short, is the first algorithmic problem that was shown to be NP-complete, and is the cornerstone of virtually all NP-completeness proofs. The SAT problem consists of deciding whether a given Boolean formula has a “solution”, in the sense of an assignment to the variables making the entire formula to evaluate to true. Over the last few years very powerful algorithms have been devised being able to solve SAT problems with hundreds of thousands of variables. For difficult (or randomly generated) formulas these algorithms can be compared to the proverbial search for the needle in a haystack. This book explains how such algorithms work, for example, by exploiting the structure of the SAT problem with an appropriate logical calculus, like resolution. But also algorithms based on “physical” principles are considered. I was delighted to see how nicely the authors were able to cover such a variety of topics with elegance. I cannot resist saying that the introduction to SAT on page 9 is absolutely the best I ever expect to see in any book! Donald E. Knuth, Stanford University This book gives lucid descriptions of algorithms for SAT that are better than you would think! A must-read for anyone in theory. William Gasarch, University of Maryland It was a wonderful surprise to see a deep mathematical analysis of important algorithms for SAT presented so clearly and concisely. This is an excellent introductory book for studying the foundations of constraint satisfaction. Osamu Watanabe, Tokyo Institute of Technology


Handbook of Satisfiability

Handbook of Satisfiability

Author: A. Biere

Publisher: IOS Press

Published: 2021-05-05

Total Pages: 1486

ISBN-13: 1643681613

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Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"


Stochastic Local Search

Stochastic Local Search

Author: Holger H. Hoos

Publisher: Morgan Kaufmann

Published: 2005

Total Pages: 678

ISBN-13: 1558608729

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Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.


Algorithms for the Satisfiability Problem

Algorithms for the Satisfiability Problem

Author: Jun Gu

Publisher:

Published: 1999

Total Pages: 250

ISBN-13: 9780521640411

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The satisfiability (SAT) problem is central in mathematical logic and computing theory, representing a core of computationally intractable NP-complete problems. It is a fundamental hurdle in solving many problems in automated reasoning, computer-aided design, computer-aided manufacturing, machine vision, database construction and maintenance, robotics, scheduling, integrated circuit design, computer architecture design, and computer networking. Efficient methods for solving the SAT problem play an important role in the development of practical computing systems. Traditional methods treat SAT as a discrete, constrained decision problem. In recent years, many optimization methods, parallel algorithms, and other practical new techniques have been developed for solving the SAT problem. This book describes these state-of-the-art methods, both sequential and parallel, and discusses tradeoffs and limitations in the rapidly growing field of satisfiability testing. It will be useful for computer theorists, algorithmists, and practitioners working in all areas in computer science, computer engineering, operations research, and applied logic.


A Survey of Lower Bounds for Satisfiability and Related Problems

A Survey of Lower Bounds for Satisfiability and Related Problems

Author: Dieter van Melkebeek

Publisher: Now Publishers Inc

Published: 2007

Total Pages: 124

ISBN-13: 1601980841

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Surveys the recently discovered lower bounds for the time and space complexity of satisfiability and closely related problems. It overviews the state-of-the-art results on general deterministic, randomized, and quantum models of computation, and presents the underlying arguments in a unified framework.


Heuristic Search

Heuristic Search

Author: Stefan Edelkamp

Publisher: Elsevier

Published: 2011-05-31

Total Pages: 865

ISBN-13: 0080919731

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Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. - Provides real-world success stories and case studies for heuristic search algorithms - Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units


Satisfiability Problem

Satisfiability Problem

Author: Dingzhu Du

Publisher: American Mathematical Soc.

Published: 1997-01-01

Total Pages: 778

ISBN-13: 9780821870808

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The satisfiability (SAT) problem is central in mathematical logic, computing theory, and many industrial applications. There has been a strong relationship between the theory, the algorithms, and the applications of the SAT problem. This book aims to bring together work by the best theorists, algorithmists, and practitioners working on the sat problem and on industrial applications, as well as to enhance the interaction between the three research groups. The book features the applications of theoretical/algorithmic results to practical problems and presents practical examples for theoretical/algoritmic study. Major topics covered in the book include practical and industial SAT problems and benchmarks, significant case studies and applications of the SAT problem and SAT algorithms, new algorithms and improved techniques for satisfiability testing, specific data structures and implementation details of the SAT algorithms, and the theoretical study of the SAT problem and SAT algorithms.


Plan, Activity, and Intent Recognition

Plan, Activity, and Intent Recognition

Author: Gita Sukthankar

Publisher: Newnes

Published: 2014-03-03

Total Pages: 423

ISBN-13: 012401710X

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Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. Plan, Activity, and Intent Recognition explains the crucial role of these techniques in a wide variety of applications including: - personal agent assistants - computer and network security - opponent modeling in games and simulation systems - coordination in robots and software agents - web e-commerce and collaborative filtering - dialog modeling - video surveillance - smart homes In this book, follow the history of this research area and witness exciting new developments in the field made possible by improved sensors, increased computational power, and new application areas. - Combines basic theory on algorithms for plan/activity recognition along with results from recent workshops and seminars - Explains how to interpret and recognize plans and activities from sensor data - Provides valuable background knowledge and assembles key concepts into one guide for researchers or students studying these disciplines


Machine Learning for Automated Theorem Proving

Machine Learning for Automated Theorem Proving

Author: Sean B. Holden

Publisher:

Published: 2021-11-22

Total Pages: 202

ISBN-13: 9781680838985

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In this book, the author presents the results of his thorough and systematic review of the research at the intersection of two apparently rather unrelated fields: Automated Theorem Proving (ATP) and Machine Learning (ML).