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# Logic for Computer Science and Artificial Intelligence. Edition No. 1

• ID: 2182843
• Book
• July 2011
• 523 Pages
• John Wiley and Sons Ltd
Logic and its components (propositional, first-order, non-classical) play a key role in Computer Science and Artificial Intelligence. While a large amount of information exists scattered throughout various media (books, journal articles, webpages, etc.), the diffuse nature of these sources is problematic and logic as a topic benefits from a unified approach. Logic for Computer Science and Artificial Intelligence utilizes this format, surveying the tableaux, resolution, Davis and Putnam methods, logic programming, as well as for example unification and subsumption. For non-classical logics, the translation method is detailed.
Logic for Computer Science and Artificial Intelligence is the classroom-tested result of several years of teaching at Grenoble INP (Ensimag). It is conceived to allow self-instruction for a beginner with basic knowledge in Mathematics and Computer Science, but is also highly suitable for use in traditional courses. The reader is guided by clearly motivated concepts, introductions, historical remarks, side notes concerning connections with other disciplines, and numerous exercises, complete with detailed solutions, The title provides the reader with the tools needed to arrive naturally at practical implementations of the concepts and techniques discussed, allowing for the design of algorithms to solve problems.
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Preface xi

Chapter 1. Introduction 1

1.1. Logic, foundations of computer science, and applications of logic to computer science 1

1.2. On the utility of logic for computer engineers 3

Chapter 2. A Few Thoughts Before the Formalization 7

2.1. What is logic? 7

2.2. Somehistoric landmarks 32

Chapter 3. Propositional Logic 39

3.1. Syntaxand semantics 40

3.2. Themethodof semantic tableaux 54

3.3. Formal systems 64

3.4. Aformal systemforPL(PC) 78

3.5. ThemethodofDavis andPutnam 92

3.6. Semantic trees inPL 96

3.7. The resolutionmethodinPL 101

3.8. Problems, strategies, andstatements 109

3.9. Hornclauses 113

3.10. Algebraic point of view of propositional logic 114

Chapter 4. First-order Terms 121

4.1. Matchingandunification 121

4.2. First-order terms, substitutions, unification 125

Chapter 5. First-Order Logic (FOL) or Predicate Logic (PL1, PC1) 131

5.1. Syntax 133

5.2. Semantics 137

5.3. Semantic tableauxin FOL 154

5.4. Unification in the method of semantic tableaux 166

5.5. Toward a semi-decision procedure for FOL 169

5.6. Semantic trees inFOL 186

5.7. The resolutionmethodinFOL 190

5.9. Limits: Godel’s (first) incompleteness theorem 206

Chapter 6. Foundations of Logic Programming 213

6.1. Specifications and programming 213

6.2. Toward a logic programming language 219

6.3. Logicprogramming: examples 222

6.4. Computability and Horn clauses 241

Chapter 7. Artificial Intelligence 245

7.1. Intelligent systems: AI 245

7.2. What approaches to studyAI? 249

7.3. Toward an operational definition of intelligence 249

7.4. Can we identify human intelligence with mechanicalintelligence? 251

7.5. Somehistory 254

7.6. Some undisputed themes in AI 256

Chapter 8. Inference 259

8.1. Deductiveinference 260

8.2. An important concept: clause subsumption 266

8.3. Abduction 273

8.4. Inductive inference 278

8.5. Generalization: the generation of inductive hypotheses 284

Chapter 9. Problem Specification in Logical Languages 291

9.1. Equality 291

9.2. Constraints 309

9.3. Second Order Logic (SOL): a few notions 319

Chapter 10. Non-classical Logics 327

10.1. Many-valuedlogics 327

10.2. Inaccurate concepts: fuzzy logic 337

10.3. Modal logics 353

10.4. Some elements of temporal logic 371

Chapter 11. Knowledge and Logic: Some Notions 385

11.1. What is knowledge? 386

11.2. Knowledge and modal logic 389

Chapter 12. Solutions to the Exercises 395

Bibliography 515

Index 517

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Ricardo Caferra
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