Handbook of satisfiability: Part 1
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| Language: | English |
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Amsterdam ; Berlin ; Washington, DC
IOS Press
[2021]
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| Series: | Frontiers in artificial intelligence and applications
Volume 336,1 |
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| Online Access: | Inhaltsverzeichnis |
| Physical Description: | xvii, 736 Seiten Illustrationen |
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| 245 | 1 | 0 | |a Handbook of satisfiability |n Part 1 |c edited by Armin Biere, Johannes Kepler University, Linz, Austria, Marijn Heule, Carnegie Mellon University, Pittsburgh, USA, Hans van Maaren, TU Delft, the Netherlands, Delft, and Toby Walsh, University of New South Wales, Kensington, Australia |
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Contents Part I. Theory and Algorithms Chapter 1. A History of Satisfiability John Franco and John Martin 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 Gödel’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 resolution Alasdair Urquhart 1.17 Refinement of Resolution-Based SAT Solvers 1.18 Upper bounds Ewald Speckenmeyer 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 Holger Hoos 1.24 Maximum Satisfiability Hantao Zhang 1.25 Nonlinear formulations Miguel Anjos 1.26 Pseudo-Boolean Forms 1.27 Quantified Boolean formulas Hans Kleine Biining References 3 3 6 8 9 10 10 12 13 14 14 15 15 17 18 19 21 23 25 27 31 32 39 42 43 45 49 51
Contents x Chapter 2. CNF Encodings Steven Prestwick 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 Algorithms Adnan Darwiche and Knot Pipatsrisawat 3.1 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 75 75 75 83 91 94 94 101 101 101 104 109 112 116 128 128 Chapter 4. CDCL SAT Solving Joao Marques-Silva, Ines Lynce and Sharad Malik Introduction 4.1 Preliminaries 4.2 Implementing CDCL SAT Solvers 4.3 4.4 Using CDCL SAT Solvers 4.5 Impact of CDCL SAT Solvers 4.6 Historical Perspective 4.7 To Probe Further 4.8 Conclusions Research Directions References 133 Chapter 5. Look-Ahead Based SAT Solvers 183 Marijn J.H. Heule and Hans van Maaren 5.1 Introduction 5.2 General and Historical Overview 5.3 Heuristics 5.4 Additional Reasoning 5.5 Eager Data-Structures References Chapter 6. Incomplete Algorithms Henry Kautz, Ashish Sabharwal and Bart Selman 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 /с-SAT: Survey Propagation 133 135 140 152 160 161 163 164 164 183 185 լցշ 201 207 οι n 213 215 218 219 222 224
Contents 6.6 Conclusion References Chapter 7. Proof Complexity and SAT Solving Sam Buss and Jakob Nordstrom 7.1 Introduction 7.2 Preliminaries 7.3 Resolution and CDCL SAT solvers 7.4 Resolution and Proof Complexity 7.5 Algebraic Proof Systems 7.6 Cutting Planes and Pseudo-В o olean Solving 7.7 Cutting Planes and Proof Complexity 7.8 Extended Resolution and DRAT Proof Systems 7.9 Frege and Extended Frege Proof Systems 7.10 Bounded-Depth Frege Proof System 7.11 Concluding Remarks References Chapter 8. Fundaments of Branching Heuristics Oliver Kullmann 8.1 Introduction 8.2 A general framework for branching algorithms Branching tuples and the canonical projection 8.3 8.4 Estimating tree sizes Axiomatising the canonical order on branching tuples 8.5 Alternative projections for restricted branching width 8.6 How to select distances and measures 8.7 Optimising distance functions 8.8 The order of branches 8.9 8.10 Beyond clause-sets 8.11 Conclusion and outlook References Chapter 9. Preprocessing in SAT Solving Armin Biere, Matti Järvisalo and Benjamin Kiesi 9.1 Introduction Classical Preprocessing Techniques 9.2 Resolution-Based Preprocessing 9.3 CNF Preprocessing Beyond Resolution 9.4 Solution Reconstruction 9.5 Structure-Based Preprocessing 9.6 9.7 Conclusion References Chapter 10. Random Satisfiability Dimitris Achlioptas 10.1 Introduction 10.2 The State of the Art 10.3 Random MAX fc-SAT 225 226 233 233 236 238 255 270 282 300 312 316 318 322 324 351 351 353 357 362 368 369 371 378 380 383 385 386 391 391 394 401 409 411 414 418 419 437 437 439 441
xii Contents 10.4 Physical Predictions for Solution-space Geometry . 10.5 The Role of the Second Moment Method 10.6 Generative models r;t І-ч» 10.7 Algorithms 10.8 Belief/Survey Propagation and the Algorithmic Barrier 10.9 Backtracking Algorithms ,. . .՛ 10.10 Exponential Running-Time for к 3 T, References Chapter 11. Exploiting Runtime Variation in Complete Solvers Carla P. Gomes and Ashish Sabharwal :v·՝ 11.1 Runtime Variation in Backtrack Search · m; ’ ■·՛ 11.2 Exploiting Runtime Variation: Randomization and Restarts 11.3 Conclusion ’,,՝■■՛■, i “Ч References ■'■֊.‘í.:· - · ՛ 444 447 447 451 454 455 457 458 463 ֊.·■ ՛■՛* Chapter 12. Automated Configuration and Selection of SAT Solvers Holger H. Hoos, Frank Hutter and Kevin Leyton-Brown 12.1 Introduction 12.2 Algorithm configuration :? 12.3 Per-instance algorithm selection 12.4 Related approaches 12.5 Conclusions and open challenges References 465 472 477 477 481 481 482 489 496 499 500 Chapter 13. Symmetry and Satisfiability Karem A. Sakallah 13.1 Motivating Example 13.2 Preliminaries 13.3 Group Theory Basics 13.4 CNF Symmetry 13.5 Automorphism Group of a Colored Graph 13.6 Detection of CNF Symmetries 13.7 Symmetry Breaking 13.8 From Symmetry to Satisfiability and Back 13.9 Summary and a Look Forward 13.10 Bibliographic Notes References 509 Chapter 14. Minimal Unsatisfiability and Autarkies Hans Kleine Biining and Oliver Kullmann 14.1 Introduction 14.2 Deficiency 14.3 Resolution and Homomorphism 14.4 Special Classes 14.5 Extension to non-clausal formulas 14.6 Minima! Falsity for QBF 14.7 Applications and Experimental
Results 571 509 512 516 525 526 531 537 548 557 560 566 571 572 575 577 580 583 585
Contents 14.8 Generalising satisfying assignments through “autarkies” 14.9 The autarky monoid 14.10 Finding and using autarkies 14.11 Autarky systems: Using weaker forms of autarkies 14.12 Connections to combinatorics 14.13 Generalisations and extensions of autarkies 14.14 Conclusion References Chapter 15. Proofs of Unsatisfiability Marijn J.H. Heule 15.1 Introduction 15.2 Proof Systems 15.3 Proof Search 15.4 Proof Formats 15.5 Proof Production in Practical SAT Solving 15.6 Proof Validation and Processing 15.7 Proof Applications 15.8 Conclusions References Chapter 16. Worst-Case Upper Bounds Evgeny Dantsin and Edward A. Hirsch 16.1 16.2 16.3 16.4 16.5 16.6 16.7 Preliminaries Tractable and intractable classes Upper bounds for /г-ЅАТ Upper bounds for General SAT How large is the exponent? Summary table Addendum for the 2nd Edition: Connections to Circuit Complexity References Chapter 17. Fixed-Parameter Tractability Marko Samer and Stefan Szeider 17.1 Introduction 17.2 Preliminaries 17.3 Parameterized SAT 17.4 Backdoor Sets 17.5 Treewidth 17.6 Further Satisfiability Parameters 17.7 Concluding Remarks References xiii 585 591 598 605 617 624 627 627 635 635 637 644 645 653 657 660 661 661 669 669 671 674 679 682 686 687 688 693 693 695 700 704 712 721 726 727 Part II. Applications and Extensions Chapter 18. Bounded Model Checking Armin Biere 18.1 Model Checking 739 739
Contents XIV Bounded Semantics Propositional Encodings Completeness Induction 18.6 Interpolation 18.7 Completeness with Interpolation 18.8 Invariant Strengthening 18.9 Related Work 18.10 Conclusion References 18.2 18.3 18.4 18.5 Chapter 19. Planning and SAT 742 743 747 749 750 753 755 755 756 757 705 Jussi Rintanen 19.1 Introduction 19.2 Classical Planning 19.3 Sequential Plans 19.4 Parallel Plans 19.5 Finding a Satisfiable Formula 19.6 Temporal Planning 19.7 Contingent P Fuming References 705 70G 707 770 775 779 781 785 Chapter 20. Software Verification 7Л Daniel Kroening 20.1 Programs use Bit-Vectors 20.2 Formal Models of Software 20.3 Turning Bit-Vector Arithmetic intoCNF 20.4 Bounded Model Checking for Software 20.5 Predicate Abstraction using SAT 20.6 Conclusion References Chapter 21. Combinatorial Designs by SAT Solvers Hantao Zhang 21.1 Introduction 21.2 Combinatoria! Design Problems 21.3 Encoding Design Theory Problems 21.4 Conclusions and Open Problems References Chapter 22. Connections to Statistical Physics Fabrizio Altarelli, Rémi Monasson, Guilhem Semerjian and Francesco Zamponi 22.1 Introduction 22.2 Phase Transitions: Basic Concepts and Illustration 22.3 Phase transitions in random CSPs 22.4 Local search algorithms 22.5 Decimation based algorithms 22.6 Conclusion 791 792 795 798 803 814 815 819 819 821 845 852 853 859 859 861 869 878 882 QQ/f
Contents References Chapter 23. MaxSAT Ghu Min Li and Felip Manyà 23.1 Introduction 23.2 Preliminaries 23.3 Branch and Bound Algorithms 23.4 Complete Inference in MaxSAT 23.5 Approximation Algorithms 23.6 The MaxSAT Evaluation 23.7 Other Contributions to MaxSAT 23.8 The MinSAT Problem 23.9 Conclusions References Chapter 24. Maximum Satisfiability Fahiem Bacchus, Matti Järvisalo and Ruben Martins 24.1 Introduction 24.2 The MaxSAT Formalism 24.3 Encodings and Applications 24.4 Modern MaxSAT Algorithms 24.5 Further Developments 24.6 Summary References Chapter 25. Model Counting Carla P. Gomes, Ashish Sabharwal and Bart Selman 25.1 Computational Complexity of Model Counting 25.2 Exact Model Counting 25.3 Approximate Model Counting 25.4 Conclusion References Chapter 26. Approximate ModelCounting Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi 26.1 Introduction 26.2 Approximate Model Counting forCNF 26.3 Handling CNF+XOR Constraints 26.4 Approximate Model Counting forDNF 26.5 Weighted Counting 26.6 Conclusion References Chapter 27. Non-Clausal SAT andATPG Rolf Drechsler, Tommi Junttila and Ilkka Niemelä 27.1 Introduction 27.2 Basic Definitions 27.3 Satisfiability Checking for Boolean Circuits 27.4 Automatic Test Pattern Generation 27.5 Conclusions XV ggtj 903 9О3 9O4 906 913 917 917 918 918 919 920 929 929 931 933 939 966 971 972 993 994 996 1003 1010 1011 1015 1015 1020 1030 1032 1035 1039 1040 1047 1047 1048 1051 1064 1080
Contents xvi References Chapter 28. Pseudo-Boolean and Cardinality Constraints Olivier Roussel and Vasco Manquinho 28.1 Introduction 28.2 Basic Definitions 28.3 Decision Problem versus Optimization Problem 28.4 Expressive Power of Cardinality and Pseudo-Boolean Constraints 28.5 Inference Rules 28.6 Current Algorithms 28.7 Conclusion References Chapter 29. QBF Theory Hans Kleine Hüning and Uwe Bubeck 29.1 Introduction 29.2 Syntax and Semantics 29.3 Complexity Results 29.4 Models and Expressive power 29.5 Q-Resolution 29.6 Quantified Horn Formulas and Q2-CNF References Chapter 30. QBFs reasoning Enrico Giunchiglia, Paolo Marin and Massimo Narizzano 30.1 Introduction v 30.2 Quantified Boolean Logic 30.3 Applications of QBFs andQBFreasoning 30.4 QBF solvers 30.5 Other approaches, extensionsandconclusions References Chapter 31. Quantified Boolean Formulas Olaf Beyersdorff, Mikoláš Janota, Florian Lousing and Martina Seidl 31.1 Introduction 31.2 Preliminaries 31.3 Proof Systems Based on Q-Resolution 31.4 Expansion-Based Proof Systems 31.5 Preprocessing 31.6 Extraction of Winning Strategies from Proofs 31.7 Connections Between Proof Systems References Chapter 32. SAT Techniques for Modal and Description Logics Roberto 32.1 32.2 32.3 32.4 Sebastiani and Armando Tacchella Introduction Background Basic Modal DPLL Advanced Modal DPLL 1080 1087 1087 1088 1091 1093 1095 1102 1125 1125 1131 1131 1131 1137 1140 IMG 1150 1154 1157 1157 1157 1158 1159 1172 1172 1177 П77 И78 1179 1191 ļļgg 1204 1207 i .) і r 1223 1223 1225 1231 1242
Contents xvii 32.5 The OBDD-based Approach 32.6 The Eager DPLL-based approach References 1252 1256 1261 Chapter 33. Satisfiability Modulo Theories Clark Barrett, Roberto Sebastiani, Sanjit A. Seshia and Cesare Tinelli 33.1 Introduction 33.2 Background 33.3 Eager Encodings to SAT 33.4 Integrating Theory Solvers into SAT Engines 33.5 Theory Solvers 33.6 Combining Theories 33.7 Extensions and Enhancements References Chapter 34. Stochastic Boolean Satisfiability Stephen M. Majercik 34.1 Introduction 34.2 Definitions and Notation 34.3 Complexity of SSAT and Related Problems 34.4 Applications 34.5 Analytical Results 34.6 Algorithms and Empirical Results 34.7 Stochastic Constraint Programming 34.8 Future Directions References 1267 1267 1269 1275 1285 1297 1303 1310 1316 1331 1331 1331 1334 1335 1336 1337 1354 1356 1363 Subject Index 1371 Cited Author Index 1429 Contributing Authors and Affiliations 1463 |
| adam_txt |
Contents Part I. Theory and Algorithms Chapter 1. A History of Satisfiability John Franco and John Martin 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 Gödel’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 resolution Alasdair Urquhart 1.17 Refinement of Resolution-Based SAT Solvers 1.18 Upper bounds Ewald Speckenmeyer 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 Holger Hoos 1.24 Maximum Satisfiability Hantao Zhang 1.25 Nonlinear formulations Miguel Anjos 1.26 Pseudo-Boolean Forms 1.27 Quantified Boolean formulas Hans Kleine Biining References 3 3 6 8 9 10 10 12 13 14 14 15 15 17 18 19 21 23 25 27 31 32 39 42 43 45 49 51
Contents x Chapter 2. CNF Encodings Steven Prestwick 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 Algorithms Adnan Darwiche and Knot Pipatsrisawat 3.1 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 75 75 75 83 91 94 94 101 101 101 104 109 112 116 128 128 Chapter 4. CDCL SAT Solving Joao Marques-Silva, Ines Lynce and Sharad Malik Introduction 4.1 Preliminaries 4.2 Implementing CDCL SAT Solvers 4.3 4.4 Using CDCL SAT Solvers 4.5 Impact of CDCL SAT Solvers 4.6 Historical Perspective 4.7 To Probe Further 4.8 Conclusions Research Directions References 133 Chapter 5. Look-Ahead Based SAT Solvers 183 Marijn J.H. Heule and Hans van Maaren 5.1 Introduction 5.2 General and Historical Overview 5.3 Heuristics 5.4 Additional Reasoning 5.5 Eager Data-Structures References Chapter 6. Incomplete Algorithms Henry Kautz, Ashish Sabharwal and Bart Selman 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 /с-SAT: Survey Propagation 133 135 140 152 160 161 163 164 164 183 185 լցշ 201 207 οι n 213 215 218 219 222 224
Contents 6.6 Conclusion References Chapter 7. Proof Complexity and SAT Solving Sam Buss and Jakob Nordstrom 7.1 Introduction 7.2 Preliminaries 7.3 Resolution and CDCL SAT solvers 7.4 Resolution and Proof Complexity 7.5 Algebraic Proof Systems 7.6 Cutting Planes and Pseudo-В o olean Solving 7.7 Cutting Planes and Proof Complexity 7.8 Extended Resolution and DRAT Proof Systems 7.9 Frege and Extended Frege Proof Systems 7.10 Bounded-Depth Frege Proof System 7.11 Concluding Remarks References Chapter 8. Fundaments of Branching Heuristics Oliver Kullmann 8.1 Introduction 8.2 A general framework for branching algorithms Branching tuples and the canonical projection 8.3 8.4 Estimating tree sizes Axiomatising the canonical order on branching tuples 8.5 Alternative projections for restricted branching width 8.6 How to select distances and measures 8.7 Optimising distance functions 8.8 The order of branches 8.9 8.10 Beyond clause-sets 8.11 Conclusion and outlook References Chapter 9. Preprocessing in SAT Solving Armin Biere, Matti Järvisalo and Benjamin Kiesi 9.1 Introduction Classical Preprocessing Techniques 9.2 Resolution-Based Preprocessing 9.3 CNF Preprocessing Beyond Resolution 9.4 Solution Reconstruction 9.5 Structure-Based Preprocessing 9.6 9.7 Conclusion References Chapter 10. Random Satisfiability Dimitris Achlioptas 10.1 Introduction 10.2 The State of the Art 10.3 Random MAX fc-SAT 225 226 233 233 236 238 255 270 282 300 312 316 318 322 324 351 351 353 357 362 368 369 371 378 380 383 385 386 391 391 394 401 409 411 414 418 419 437 437 439 441
xii Contents 10.4 Physical Predictions for Solution-space Geometry . 10.5 The Role of the Second Moment Method 10.6 Generative models r;t І-ч» 10.7 Algorithms 10.8 Belief/Survey Propagation and the Algorithmic Barrier 10.9 Backtracking Algorithms ,. . .՛ 10.10 Exponential Running-Time for к 3 T, References Chapter 11. Exploiting Runtime Variation in Complete Solvers Carla P. Gomes and Ashish Sabharwal :v·՝ 11.1 Runtime Variation in Backtrack Search · m; ’ ■·՛ 11.2 Exploiting Runtime Variation: Randomization and Restarts 11.3 Conclusion ’,,՝■■՛■, i “Ч References ■'■֊.‘í.:· - · ՛ 444 447 447 451 454 455 457 458 463 ֊.·■ ՛■՛* Chapter 12. Automated Configuration and Selection of SAT Solvers Holger H. Hoos, Frank Hutter and Kevin Leyton-Brown 12.1 Introduction 12.2 Algorithm configuration :? 12.3 Per-instance algorithm selection 12.4 Related approaches 12.5 Conclusions and open challenges References 465 472 477 477 481 481 482 489 496 499 500 Chapter 13. Symmetry and Satisfiability Karem A. Sakallah 13.1 Motivating Example 13.2 Preliminaries 13.3 Group Theory Basics 13.4 CNF Symmetry 13.5 Automorphism Group of a Colored Graph 13.6 Detection of CNF Symmetries 13.7 Symmetry Breaking 13.8 From Symmetry to Satisfiability and Back 13.9 Summary and a Look Forward 13.10 Bibliographic Notes References 509 Chapter 14. Minimal Unsatisfiability and Autarkies Hans Kleine Biining and Oliver Kullmann 14.1 Introduction 14.2 Deficiency 14.3 Resolution and Homomorphism 14.4 Special Classes 14.5 Extension to non-clausal formulas 14.6 Minima! Falsity for QBF 14.7 Applications and Experimental
Results 571 509 512 516 525 526 531 537 548 557 560 566 571 572 575 577 580 583 585
Contents 14.8 Generalising satisfying assignments through “autarkies” 14.9 The autarky monoid 14.10 Finding and using autarkies 14.11 Autarky systems: Using weaker forms of autarkies 14.12 Connections to combinatorics 14.13 Generalisations and extensions of autarkies 14.14 Conclusion References Chapter 15. Proofs of Unsatisfiability Marijn J.H. Heule 15.1 Introduction 15.2 Proof Systems 15.3 Proof Search 15.4 Proof Formats 15.5 Proof Production in Practical SAT Solving 15.6 Proof Validation and Processing 15.7 Proof Applications 15.8 Conclusions References Chapter 16. Worst-Case Upper Bounds Evgeny Dantsin and Edward A. Hirsch 16.1 16.2 16.3 16.4 16.5 16.6 16.7 Preliminaries Tractable and intractable classes Upper bounds for /г-ЅАТ Upper bounds for General SAT How large is the exponent? Summary table Addendum for the 2nd Edition: Connections to Circuit Complexity References Chapter 17. Fixed-Parameter Tractability Marko Samer and Stefan Szeider 17.1 Introduction 17.2 Preliminaries 17.3 Parameterized SAT 17.4 Backdoor Sets 17.5 Treewidth 17.6 Further Satisfiability Parameters 17.7 Concluding Remarks References xiii 585 591 598 605 617 624 627 627 635 635 637 644 645 653 657 660 661 661 669 669 671 674 679 682 686 687 688 693 693 695 700 704 712 721 726 727 Part II. Applications and Extensions Chapter 18. Bounded Model Checking Armin Biere 18.1 Model Checking 739 739
Contents XIV Bounded Semantics Propositional Encodings Completeness Induction 18.6 Interpolation 18.7 Completeness with Interpolation 18.8 Invariant Strengthening 18.9 Related Work 18.10 Conclusion References 18.2 18.3 18.4 18.5 Chapter 19. Planning and SAT 742 743 747 749 750 753 755 755 756 757 705 Jussi Rintanen 19.1 Introduction 19.2 Classical Planning 19.3 Sequential Plans 19.4 Parallel Plans 19.5 Finding a Satisfiable Formula 19.6 Temporal Planning 19.7 Contingent P Fuming References 705 70G 707 770 775 779 781 785 Chapter 20. Software Verification 7Л Daniel Kroening 20.1 Programs use Bit-Vectors 20.2 Formal Models of Software 20.3 Turning Bit-Vector Arithmetic intoCNF 20.4 Bounded Model Checking for Software 20.5 Predicate Abstraction using SAT 20.6 Conclusion References Chapter 21. Combinatorial Designs by SAT Solvers Hantao Zhang 21.1 Introduction 21.2 Combinatoria! Design Problems 21.3 Encoding Design Theory Problems 21.4 Conclusions and Open Problems References Chapter 22. Connections to Statistical Physics Fabrizio Altarelli, Rémi Monasson, Guilhem Semerjian and Francesco Zamponi 22.1 Introduction 22.2 Phase Transitions: Basic Concepts and Illustration 22.3 Phase transitions in random CSPs 22.4 Local search algorithms 22.5 Decimation based algorithms 22.6 Conclusion 791 792 795 798 803 814 815 819 819 821 845 852 853 859 859 861 869 878 882 QQ/f
Contents References Chapter 23. MaxSAT Ghu Min Li and Felip Manyà 23.1 Introduction 23.2 Preliminaries 23.3 Branch and Bound Algorithms 23.4 Complete Inference in MaxSAT 23.5 Approximation Algorithms 23.6 The MaxSAT Evaluation 23.7 Other Contributions to MaxSAT 23.8 The MinSAT Problem 23.9 Conclusions References Chapter 24. Maximum Satisfiability Fahiem Bacchus, Matti Järvisalo and Ruben Martins 24.1 Introduction 24.2 The MaxSAT Formalism 24.3 Encodings and Applications 24.4 Modern MaxSAT Algorithms 24.5 Further Developments 24.6 Summary References Chapter 25. Model Counting Carla P. Gomes, Ashish Sabharwal and Bart Selman 25.1 Computational Complexity of Model Counting 25.2 Exact Model Counting 25.3 Approximate Model Counting 25.4 Conclusion References Chapter 26. Approximate ModelCounting Supratik Chakraborty, Kuldeep S. Meel and Moshe Y. Vardi 26.1 Introduction 26.2 Approximate Model Counting forCNF 26.3 Handling CNF+XOR Constraints 26.4 Approximate Model Counting forDNF 26.5 Weighted Counting 26.6 Conclusion References Chapter 27. Non-Clausal SAT andATPG Rolf Drechsler, Tommi Junttila and Ilkka Niemelä 27.1 Introduction 27.2 Basic Definitions 27.3 Satisfiability Checking for Boolean Circuits 27.4 Automatic Test Pattern Generation 27.5 Conclusions XV ggtj 903 9О3 9O4 906 913 917 917 918 918 919 920 929 929 931 933 939 966 971 972 993 994 996 1003 1010 1011 1015 1015 1020 1030 1032 1035 1039 1040 1047 1047 1048 1051 1064 1080
Contents xvi References Chapter 28. Pseudo-Boolean and Cardinality Constraints Olivier Roussel and Vasco Manquinho 28.1 Introduction 28.2 Basic Definitions 28.3 Decision Problem versus Optimization Problem 28.4 Expressive Power of Cardinality and Pseudo-Boolean Constraints 28.5 Inference Rules 28.6 Current Algorithms 28.7 Conclusion References Chapter 29. QBF Theory Hans Kleine Hüning and Uwe Bubeck 29.1 Introduction 29.2 Syntax and Semantics 29.3 Complexity Results 29.4 Models and Expressive power 29.5 Q-Resolution 29.6 Quantified Horn Formulas and Q2-CNF References Chapter 30. QBFs reasoning Enrico Giunchiglia, Paolo Marin and Massimo Narizzano 30.1 Introduction v 30.2 Quantified Boolean Logic 30.3 Applications of QBFs andQBFreasoning 30.4 QBF solvers 30.5 Other approaches, extensionsandconclusions References Chapter 31. Quantified Boolean Formulas Olaf Beyersdorff, Mikoláš Janota, Florian Lousing and Martina Seidl 31.1 Introduction 31.2 Preliminaries 31.3 Proof Systems Based on Q-Resolution 31.4 Expansion-Based Proof Systems 31.5 Preprocessing 31.6 Extraction of Winning Strategies from Proofs 31.7 Connections Between Proof Systems References Chapter 32. SAT Techniques for Modal and Description Logics Roberto 32.1 32.2 32.3 32.4 Sebastiani and Armando Tacchella Introduction Background Basic Modal DPLL Advanced Modal DPLL 1080 1087 1087 1088 1091 1093 1095 1102 1125 1125 1131 1131 1131 1137 1140 IMG 1150 1154 1157 1157 1157 1158 1159 1172 1172 1177 П77 И78 1179 1191 ļļgg 1204 1207 i .) і r 1223 1223 1225 1231 1242
Contents xvii 32.5 The OBDD-based Approach 32.6 The Eager DPLL-based approach References 1252 1256 1261 Chapter 33. Satisfiability Modulo Theories Clark Barrett, Roberto Sebastiani, Sanjit A. Seshia and Cesare Tinelli 33.1 Introduction 33.2 Background 33.3 Eager Encodings to SAT 33.4 Integrating Theory Solvers into SAT Engines 33.5 Theory Solvers 33.6 Combining Theories 33.7 Extensions and Enhancements References Chapter 34. Stochastic Boolean Satisfiability Stephen M. Majercik 34.1 Introduction 34.2 Definitions and Notation 34.3 Complexity of SSAT and Related Problems 34.4 Applications 34.5 Analytical Results 34.6 Algorithms and Empirical Results 34.7 Stochastic Constraint Programming 34.8 Future Directions References 1267 1267 1269 1275 1285 1297 1303 1310 1316 1331 1331 1331 1334 1335 1336 1337 1354 1356 1363 Subject Index 1371 Cited Author Index 1429 Contributing Authors and Affiliations 1463 |
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| id | DE-604.BV047110935 |
| illustrated | Illustrated |
| index_date | 2024-07-03T16:26:22Z |
| indexdate | 2024-12-08T23:00:27Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032517386 |
| oclc_num | 1257808866 |
| open_access_boolean | |
| owner | DE-11 DE-473 DE-BY-UBG |
| owner_facet | DE-11 DE-473 DE-BY-UBG |
| physical | xvii, 736 Seiten Illustrationen |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | IOS Press |
| record_format | marc |
| series | Frontiers in artificial intelligence and applications |
| series2 | Frontiers in artificial intelligence and applications |
| spelling | Handbook of satisfiability Part 1 edited by Armin Biere, Johannes Kepler University, Linz, Austria, Marijn Heule, Carnegie Mellon University, Pittsburgh, USA, Hans van Maaren, TU Delft, the Netherlands, Delft, and Toby Walsh, University of New South Wales, Kensington, Australia Amsterdam ; Berlin ; Washington, DC IOS Press [2021] xvii, 736 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Frontiers in artificial intelligence and applications Volume 336,1 Frontiers in artificial intelligence and applications Erfüllbarkeitsproblem (DE-588)4323820-8 gnd rswk-swf Erfüllbarkeitsproblem (DE-588)4323820-8 s DE-604 Biere, Armin 1967- Sonstige (DE-588)115751823 oth Heule, Marijn J. H. 1979- Sonstige (DE-588)1078931380 oth Maaren, Hans van 1950- Sonstige (DE-588)142180874 oth (DE-604)BV047110920 1 Frontiers in artificial intelligence and applications Volume 336,1 (DE-604)BV009804456 336,1 Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032517386&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Handbook of satisfiability Frontiers in artificial intelligence and applications Erfüllbarkeitsproblem (DE-588)4323820-8 gnd |
| subject_GND | (DE-588)4323820-8 |
| title | Handbook of satisfiability |
| title_auth | Handbook of satisfiability |
| title_exact_search | Handbook of satisfiability |
| title_exact_search_txtP | Handbook of satisfiability |
| title_full | Handbook of satisfiability Part 1 edited by Armin Biere, Johannes Kepler University, Linz, Austria, Marijn Heule, Carnegie Mellon University, Pittsburgh, USA, Hans van Maaren, TU Delft, the Netherlands, Delft, and Toby Walsh, University of New South Wales, Kensington, Australia |
| title_fullStr | Handbook of satisfiability Part 1 edited by Armin Biere, Johannes Kepler University, Linz, Austria, Marijn Heule, Carnegie Mellon University, Pittsburgh, USA, Hans van Maaren, TU Delft, the Netherlands, Delft, and Toby Walsh, University of New South Wales, Kensington, Australia |
| title_full_unstemmed | Handbook of satisfiability Part 1 edited by Armin Biere, Johannes Kepler University, Linz, Austria, Marijn Heule, Carnegie Mellon University, Pittsburgh, USA, Hans van Maaren, TU Delft, the Netherlands, Delft, and Toby Walsh, University of New South Wales, Kensington, Australia |
| title_short | Handbook of satisfiability |
| title_sort | handbook of satisfiability |
| topic | Erfüllbarkeitsproblem (DE-588)4323820-8 gnd |
| topic_facet | Erfüllbarkeitsproblem |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032517386&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV047110920 (DE-604)BV009804456 |
| work_keys_str_mv | AT bierearmin handbookofsatisfiabilitypart1 AT heulemarijnjh handbookofsatisfiabilitypart1 AT maarenhansvan handbookofsatisfiabilitypart1 |