Symbolic logic and mechanical theorem proving


Symbolic logic and mechanical theorem proving

Chin-Liang Chang, Richard Char-Tung Lee

(Computer science and applied mathematics)

Academic Press, c1973

大学図書館所蔵 件 / 76



Bibliography: p. 309-324

Includes index



This book contains an introduction to symbolic logic and a thorough discussion of mechanical theorem proving and its applications. The book consists of three major parts. Chapters 2 and 3 constitute an introduction to symbolic logic. Chapters 4-9 introduce several techniques in mechanical theorem proving, and Chapters 10 an 11 show how theorem proving can be applied to various areas such as question answering, problem solving, program analysis, and program synthesis.


Preface Acknowledgments 1. Introduction 1.1 Artificial Intelligence, Symbolic Logic, and Theorem Proving 1.2 Mathematical Background References 2. The Propositional Logic 2.1 Introduction 2.2 Interpretations of Formulas in the Propositional Logic 2.3 Validity and Inconsistency in the Propositional Logic 2.4 Normal Forms in the Propositional Logic 2.5 Logical Consequences 2.6 Applications of the Propositional Logic References Exercises 3. The First-Order Logic 3.1 Introduction 3.2 Interpretations of Formulas in the First-Order Logic 3.3 Prenex Normal Forms in the First-Order Logic 3.4 Applications of the First-Order Logic References Exercises 4. Herbrand's Theorem 4.1 Introduction 4.2 Skolem Standard Forms 4.3 The Herbrand Universe of a Set of Clauses 4.4 Semantic Trees 4.5 Herbrand's Theorem 4.6 Implementation of Herbrand's Theorem References Exercises 5. The Resolution Principle 5.1 Introduction 5.2 The Resolution Principle for the Propositional Logic 5.3 Substitution and Unification 5.4 Unification Algorithm 5.5 The Resolution Principle for the First-Order Logic 5.6 Completeness of the Resolution Principle 5.7 Examples Using the Resolution Principle 5.8 Deletion Strategy References Exercises 6. Semantic Resolution and Lock Resolution 6.1 Introduction 6.2 An Informal Introduction to Semantic Resolution 6.3 Formal Definitions and Examples of Semantic Resolution 6.4 Completeness of Semantic Resolution 6.5 Hyperresolution and the Set-of-Support Strategy: Special Cases of Semantic Resolution 6.6 Semantic Resolution Using Ordered Clauses 6.7 Implementation of Semantic Resolution 6.8 Lock Resolution 6.9 Completeness of Lock Resolution References Exercises 7. Linear Resolution 7.1 Introduction 7.2 Linear Resolution 7.3 Input Resolution and Unit Resolution 7.4 Linear Resolution Using Ordered Clauses and the Information of Resolved Literals 7.5 Completeness of Linear Resolution 7.6 Linear Deduction and Tree Searching 7.7 Heuristics in Tree Searching 7.8 Estimations of Evaluation Functions References Exercises 8. The Equality Relation 8.1 Introduction 8.2 Unsatisfiability under Special Classes of Models 8.3 Paramodulation-An Inference Rule for Equality 8.4 Hyperparamodulation 8.5 Input and Unit Paramodulations 8.6 Linear Paramodulation References Exercises 9. Some Proof Procedures Based on Herbrand's Theorem 9.1 Introduction 9.2 The Prawitz Procedure 9.3 The V-Resolution Procedure 9.4 Pseudosemantic Trees 9.5 A Procedure for Generating Closed Pseudosemantic Trees 9.6 A Generalization of the Splitting Rule of Davis and Putnam References Exercises 10. Program Analysis 10.1 Introduction 10.2 An Informal Discussion 10.3 Formal Definitions of Programs 10.4 Logical Formulas Describing the Execution of a Program 10.5 Program Analysis by Resolution 10.6 The Termination and Response of Programs 10.7 The Set-of-Support Strategy and the Deduction of the Halting Clause 10.8 The Correctness and Equivalence of Programs 10.9 The Specialization of Programs References Exercises 11. Deductive Question Answering, Problem Solving, and Program Synthesis 11.1 Introduction 11.2 Class A Questions 11.3 Class B Questions 11.4 Class C Questions 11.5 Class D Questions 11.6 Completeness of Resolution for Deriving Answers 11.7 The Principles of Program Synthesis 11.8 Primitive Resolution and Algorithm A (A Program-Synthesizing Algorithm) 11.9 The Correctness of Algorithm A 11.10 The Application of Induction Axioms to Program Synthesis 11.11 Algorithm A (An Improved Program-Synthesizing Algorithm) References Exercises 12. Concluding Remarks References Appendix A A.1 A Computer Program Using Unit Binary Resolution A.2 Brief Comments on the Program A.3 A Listing of the Program A.4 Illustrations References Appendix B Bibliography Index

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