Part i The Prolog Language 1 Introduction to Prolog 2 Syntax and Meaning of Prolog Programs 3 Lists, Operators, Arithmetic 4 Programming Examples 5 Controlling Backtracking 6 Built-in Predicates 7 Constraint Logic Programming 8 Programming Style and Technique 9 Operations on Data Structures 10 Balanced Trees Part ii Prolog in Artificial Intelligence 11 Problem-Solving as Search 12 Heuristic Search and A* Algorithm 13 Best-First Search: Minimising Time and Space 14 Problem Decomposition and AND/OR Graphs 15 Knowledge Representation and Expert Systems 16 Probabilistic Reasoning with Bayesian Networks 17 Planning 18 Partial order planning and GRAPHPLAN 19 Scheduling, Simulation and Control with CLP 20 Machine Learning 21 Inductive Logic Programming 22 Qualitative Reasoning 23 Language Processing with Grammar Rules 24 Game Playing 25 Meta-Programming Appendix A: Some Differences Between Prolog Implementations Appendix B: Some Frequently Used Predicates Solutions to Selected Exercises Index
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.
Professor Ivan Bratko leads the AI Lab in the Faculty of Computer and Information Science at Ljubljana University. He has taught Prolog world-wide as well as applying Prolog in medical expert systems, robot programming, qualitative modelling and computer chess research.
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