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Handbook of Satisfiability : Handbook of Satisfiability.
"Satisfiability (SAT) related topics have attracted researchers from various disciplines: logic, applied areas such as planning, scheduling, operations research and combinatorial optimization, but also theoretical issues on the theme of complexity and much more, they all are connected through S...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam :
IOS Press,
2009.
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| Colección: | Frontiers in artificial intelligence and applications.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Title page; Contents; Part I. Theory and Algorithms; Chapter 1. A History of Satisfiability; 1.1 Preface: the concept of satisfiability; 1.2 The ancients; 1.3 The medieval period; 1.4 The renaissance; 1.5 The first logic machine; 1.6 Boolean algebra; 1.7 Frege, logicism, and quantification logic; 1.8 Russell and Whitehead; 1.9 G""odel's incompleteness theorem; 1.10 Effective process and recursive functions; 1.11 Herbrand's theorem; 1.12 Model theory and Satisfiability; 1.13 Completeness of first-order logic; 1.14 Application of logic to circuits; 1.15 Resolution.
- 1.16 The complexity or resolution1.17 Refinement of Resolution-Based SAT Solvers; 1.18 Upper bounds; 1.19 Classes of easy expressions; 1.20 Binary Decision Diagrams; 1.21 Probabilistic analysis: SAT algorithms; 1.22 Probabilistic analysis: thresholds; 1.23 Stochastic Local Search; 1.24 Maximum Satisfiability; 1.25 Nonlinear formulations; 1.26 Pseudo-Boolean Forms; 1.27 Quantified Boolean formulas; References; Chapter 2. CNF Encodings; 2.1 Introduction; 2.2 Transformation to CNF; 2.3 Case studies; 2.4 Desirable properties of CNF encodings; 2.5 Conclusion; References.
- Chapter 3. Complete Algorithms3.1 Introduction; 3.2 Technical Preliminaries; 3.3 Satisfiability by Existential Quantification; 3.4 Satisfiability by Inference Rules; 3.5 Satisfiability by Search: The DPLL Algorithm; 3.6 Satisfiability by Combining Search and Inference; 3.7 Conclusions; References; Chapter 4. CDCL Solvers; 4.1 Introduction; 4.2 Notation; 4.3 Organization of CDCL Solvers; 4.4 Conflict Analysis; 4.5 Modern CDCL Solvers; 4.6 Bibliographical and Historical Notes; References; Chapter 5. Look-Ahead Based SAT Solvers; 5.1 Introduction; 5.2 General and Historical Overview.
- 5.3 Heuristics5.4 Additional Reasoning; 5.5 Eager Data-Structures; References; Chapter 6. Incomplete Algorithms; 6.1 Greedy Search and Focused Random Walk; 6.2 Extensions of the Basic Local Search Method; 6.3 Discrete Lagrangian Methods; 6.4 The Phase Transition Phenomenon in Random k-SAT; 6.5 A New Technique for Random k-SAT: Survey Propagation; 6.6 Conclusion; References; Chapter 7. Fundaments of Branching Heuristics; 7.1 Introduction; 7.2 A general framework for branching algorithms; 7.3 Branching tuples and the canonical projection; 7.4 Estimating tree sizes.
- 7.5 Axiomatising the canonical order on branching tuples7.6 Alternative projections for restricted branching width; 7.7 How to select distances and measures; 7.8 Optimising distance functions; 7.9 The order of branches; 7.10 Beyond clause-sets; 7.11 Conclusion and outlook; References; Chapter 8. Random Satisfiability; 8.1 Introduction; 8.2 The State of the Art; 8.3 Random MAX k-SAT; 8.4 Physical Predictions for Solution-space Geometry; 8.5 The Role of the Second Moment Method; 8.6 Generative models; 8.7 Algorithms; 8.8 Belief/Survey Propagation and the Algorithmic Barrier.