Includes bibliographical references and index.

Preface -- 1. Introduction -- 2. Symbolic (Computational) Logic -- 3. AI Programming Language and Development Systems-"The Tools of the Trade" -- 4. Fundamentals of PROLOG -- 5. Constraint Satisfaction Problems and PROLOG Application to Image Labeling -- 6. An AI Application Using PROLOG: Electric Power System Protection Analysis -- 7. PROLOG Applications for Structural Object Description, Formal Languages and Parsing -- 8. Fundamentals of LISP -- 9. List of Structures-Rationale and Computer Representations -- 10. Matching and Unification in LISP-A Prelude to Rule-based Inference -- 11. Rule-based Inference Systems Part I-Production Systems, Forward Chaining, and LISP Implementations --12. Rule-based Inference Systems Part II-Backward Chaining with LISP Implementation -- 13. Inference Systems-A Further Look -- 14. Planning in AI Systems -- 15. Search and Communicational Complexity in AI Systems -- 16. Structured Knowledge Representation and Manipulation (Frames, Blackboards, and Advanced Control Concepts) -- 17. Temporal Logic and Reasoning in Artificial Intelligence -- 18. Learning in AI Systems -- 19. AI System Architecture -- Appendices -- Epilogue -- Index.

This textbook is for an advanced undergraduate or postgraduate course in artificial intelligence. No previous experience in this area is assumed. The text emphasizes the conceptual approach, while underlying mathematical and conceptual fundamentals are stressed to prepare students to participate in "hands-on" development of AI systems. Current topics of interest to the engineering community are discussed, including parallel decomposition of AI algorithms, corresponding parallel dedicated processing hardware, temporal reasoning, constant satisfaction and rule based implementations.