Prolog Programming for Artificial Intelligence, 4th edition

Published by Addison-Wesley (August 24, 2011) © 2012

  • Ivan Bratko University of Ljubljana
£67.99

  • A print text (hardcover or paperback)
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The fourth edition of this best-selling guide to Prolog and Artificial Intelligence has been updated to include key developments in the field while retaining its lucid approach to these topics. New and extended topics include Constraint Logic Programming, abductive reasoning and partial order planning.

Divided into two parts, the first part of the book introduces the programming language Prolog, while the second part teaches Artificial Intelligence using Prolog as a tool for the implementation of AI techniques.
This textbook is meant to teach Prolog as a practical programming tool and so it concentrates on the art of using the basic mechanisms of Prolog to solve interesting problems. The fourth edition has been fully revised and extended to provide an even greater range of applications, making it a self-contained guide to Prolog, AI or AI Programming for students and professional programmers.

  • 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
  • Coverage of Constraint Logic Programming (CLP) is extended and now introduced earlier in the book, in the Prolog part.
  • Most of the existing chapters on AI techniques have been systematically improved and updated
  • Coverage of planning methods is deepened in a new chapter that includes implementations of partial order planning and the GRAPHPLAN approach
  • The treatment of search methods now includes an RTA* program (real-time A* search)
  • The chapter on meta-pogramming (now chapter 25) is extended by abductive reasoning, query-the-user facility, and a sketch of CLP interpreter, all implemented as Prolog meta-interpreters
  • Programming examples are refreshed throughout the book, making them more interesting and practical. One such example introduces semantic reasoning with the well-known lexical database WordNet®.

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 

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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