| |
| |
| Preface | |
| |
| |
| Publisher's Acknowledgements | |
| |
| |
| |
| Artificial Intelligence: Its Roots and Scope | |
| |
| |
| |
| Al: History and Applications | |
| |
| |
| |
| From Eden to ENIAC: Attitudes toward Intelligence, Knowledge, and Human Artifice | |
| |
| |
| |
| Overview of AI Application Areas | |
| |
| |
| |
| Artificial Intelligence--A Summary | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Artificial Intelligence as Representation and Search | |
| |
| |
| |
| The Predicate Calculus | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| The Propositional Calculus | |
| |
| |
| |
| The Predicate Calculus | |
| |
| |
| |
| Using Inference Rules to Produce Predicate Calculus Expressions | |
| |
| |
| |
| Application: A Logic-Based Financial Advisor | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Structures and Strategies for State Space Search | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| Graph Theory | |
| |
| |
| |
| Strategies for State Space Search | |
| |
| |
| |
| Using the State Space to Represent Reasoning with the Predicate Calculus | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Heuristic Search | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| An Algorithm for Heuristic Search | |
| |
| |
| |
| Admissibility, Monotonicity, and Informedness | |
| |
| |
| |
| Using Heuristics in Games | |
| |
| |
| |
| Complexity Issues | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Control and Implementation of State Space Search | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| Recursion-Based Search | |
| |
| |
| |
| Pattern-Directed Search | |
| |
| |
| |
| Production Systems | |
| |
| |
| |
| The Blackboard Architecture for Problem Solving | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Representation and Intelligence: The AI Challenge | |
| |
| |
| |
| Knowledge Representation | |
| |
| |
| |
| Issues in Knowledge Representation | |
| |
| |
| |
| A Brief History of AI Representational Systems | |
| |
| |
| |
| Conceptual Graphs: A Network Language | |
| |
| |
| |
| Alternatives to Explicit Representation | |
| |
| |
| |
| Agent Based and Distributed Problem Solving | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Strong Method Problem Solving | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| Overview of Expert System Technology | |
| |
| |
| |
| Rule-Based Expert Systems | |
| |
| |
| |
| Model-Based, Case Based, and Hybrid Systems | |
| |
| |
| |
| Planning | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Reasoning in Uncertain Situations | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| Logic-Based Abductive Inference | |
| |
| |
| |
| Abduction: Alternatives to Logic | |
| |
| |
| |
| The Stochastic Approach to Uncertainty | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Machine Learning | |
| |
| |
| |
| Machine Learning: Symbol-based | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| A Framework for Symbol-based Learning | |
| |
| |
| |
| Version Space Search | |
| |
| |
| |
| The ID3 Decision Tree Induction Algorithm | |
| |
| |
| |
| Inductive Bias and Learnability | |
| |
| |
| |
| Knowledge and Learning | |
| |
| |
| |
| Unsupervised Learning | |
| |
| |
| |
| Reinforcement Learning | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Machine Learning: Connectionist | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| Foundations for Connectionist Networks | |
| |
| |
| |
| Perceptron Learning | |
| |
| |
| |
| Backpropagation Learning | |
| |
| |
| |
| Competitive Learning | |
| |
| |
| |
| Hebbian Coincidence Learning | |
| |
| |
| |
| Attractor Networks or "Memories" | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Machine Learning: Social and Emergent | |
| |
| |
| |
| Social and Emergent Models of Learning | |
| |
| |
| |
| The Genetic Algorithm | |
| |
| |
| |
| Classifier Systems and Genetic Programming | |
| |
| |
| |
| Artificial Life and Society-Based Learning | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Advanced Topics for AI Problem Solving | |
| |
| |
| |
| Automated Reasoning | |
| |
| |
| |
| Introduction to Weak Methods in Theorem Proving | |
| |
| |
| |
| The General Problem Solver and Difference Tables | |
| |
| |
| |
| Resolution Theorem Proving | |
| |
| |
| |
| PROLOG and Automated Reasoning | |
| |
| |
| |
| Further Issues in Automated Reasoning | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Understanding Natural Language | |
| |
| |
| |
| Role of Knowledge in Language Understanding | |
| |
| |
| |
| Deconstructing Language: A Symbolic Analysis | |
| |
| |
| |
| Syntax | |
| |
| |
| |
| Syntax and Knowledge with ATN Parsers | |
| |
| |
| |
| Stochastic Tools for Language Analysis | |
| |
| |
| |
| Natural Language Applications | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Languages and Programming Techniques for Artificial Intelligence | |
| |
| |
| |
| An Introduction to Prolog | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| Syntax for Predicate Calculus Programming | |
| |
| |
| |
| Abstract Data Types (ADTs) in PROLOG | |
| |
| |
| |
| A Production System Example in PROLOG | |
| |
| |
| |
| Designing Alternative Search Strategies | |
| |
| |
| |
| A PROLOG Planner | |
| |
| |
| |
| PROLOG: Meta-Predicates, Types, and Unification | |
| |
| |
| |
| Meta-Interpreters in PROLOG | |
| |
| |
| |
| Learning Algorithms in PROLOG | |
| |
| |
| |
| Natural Language Processing in PROLOG | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| An Introduction to LISP | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| LISP: A Brief Overview | |
| |
| |
| |
| Search in LISP: A Functional Approach to the Farmer, Wolf, Goat, and Cabbage Problem | |
| |
| |
| |
| Higher-Order Functions and Procedural Abstraction | |
| |
| |
| |
| Search Strategies in LISP | |
| |
| |
| |
| Pattern Matching in LISP | |
| |
| |
| |
| A Recursive Unification Function | |
| |
| |
| |
| Interpreters and Embedded Languages | |
| |
| |
| |
| Logic Programming in LISP | |
| |
| |
| |
| Streams and Delayed Evaluation | |
| |
| |
| |
| An Expert System Shell in LISP | |
| |
| |
| |
| Semantic Networks and Inheritance in LISP | |
| |
| |
| |
| Object-Oriented Programming Using CLOS | |
| |
| |
| |
| Learning in LISP: The ID3 Algorithm | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| |
| Exercises | |
| |
| |
| |
| Epilogue | |
| |
| |
| |
| Artificial Intelligence as Empirical Enquiry | |
| |
| |
| |
| Introduction | |
| |
| |
| |
| Artificial Intelligence: A Revised Definition | |
| |
| |
| |
| The Science of Intelligent Systems | |
| |
| |
| |
| AI: Current Issues and Future Directions | |
| |
| |
| |
| Epilogue and References | |
| |
| |
| Bibliography | |
| |
| |
| Author Index | |
| |
| |
| Subject Index | |