Prolog Programming for Artificial Intelligence (with toc)

This best-selling guide to Prolog and Artificial Intelligence, which has been updated to include key developments in the field, concentrates on the art of using the basic mechanisms of Prolog to solve interesting AI problems. Combined approach to Prolog and AI allows flexibility for learning and teaching. Provides a thorough representation of AI, emphasizing practical techniques and Prolog implementations. Prolog programs for use in projects and research are available for download from the companion website http://www.pearsoned.co.uk/bratko Part i The Prolog Language 3 1 Introduction to Prolog 3 2 Syntax and Meaning of Prolog Programs 32 3 Lists, Operators, Arithmetic 60 4 Programming Examples 86 5 Controlling Backtracking 126 6 Built-in Predicates 143 7 Constraint Logic Programming 177 8 Programming Style and Technique 197 9 Operations on Data Structures 221 10 Balanced Trees 246 Part ii Prolog in Artificial Intelligence 259 11 Problem-Solving as Search 261 12 Heuristic Search and A* Algorithm 280 13 Best-First Search: Minimising Time and Space 301 14 Problem Decomposition and AND/OR Graphs 318 15 Knowledge Representation and Expert Systems 343 16 Probabilistic Reasoning with Bayesian Networks 370 17 Planning 385 18 Partial order planning and GRAPHPLAN 406 19 Scheduling, Simulation and Control with CLP 429 20 Machine Learning 446 21 Inductive Logic Programming 489 22 Qualitative Reasoning 522 23 Language Processing with Grammar Rules 554 24 Game Playing 578 25 Meta-Programming 606 Appendix A: Some Differences Between Prolog Implementations 641 Appendix B: Some Frequently Used Predicates 643 Solutions to Selected Exercises 646 Index 665