Includes bibliographical references (pages 781-802) and indexes.
pt. I. Artificial Intelligence: Its Roots and Scope. 1. AI: History and Applications -- pt. II. Artificial Intelligence as Representation and Search. 2. The Predicate Calculus. 3. Structures and Strategies for State Space Search. 4. Heuristic Search. 5. Control and Implementation of State Space Search -- pt. III. Representations for Knowledge-Based Problem Solving. 6. Knowledge-Intensive Problem Solving. 7. Reasoning with Uncertain or Incomplete Information. 8. Knowledge Representation -- pt. IV. Languages and Programming Techniques for Artificial Intelligence. 9. An Introduction to PROLOG. 10. An Introduction to LISP -- pt. V. Advanced Topics for AI Problem Solving. 11. Understanding Natural Language. 12. Automated Reasoning. 13. Machine Learning: Symbol-Based. 14. Machine Learning: Connectionist. 15. Machine Learning: Social and Emergent -- pt. VI. Epilogue. 16. Artificial Intelligence as Empirical Enquiry.