Ivan Bratko

Prolog Programming for Artificial Intelligence

• Broschiertes Buch

Produktbeschreibung

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.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Pearson Education (US)
• 4 ed
• Seitenzahl: 696
• Erscheinungstermin: 31. August 2011
• Englisch
• Abmessung: 238mm x 171mm x 30mm
• Gewicht: 1156g
• ISBN-13: 9780321417466
• ISBN-10: 0321417461
• Artikelnr.: 24349088

Autorenporträt

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.

Inhaltsangabe

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