Thornton / Du Boulay | Artificial Intelligence Through Search | E-Book | www2.sack.de
E-Book

E-Book, Englisch, 365 Seiten, eBook

Thornton / Du Boulay Artificial Intelligence Through Search


1992
ISBN: 978-94-011-2836-0
Verlag: Springer Netherland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 365 Seiten, eBook

ISBN: 978-94-011-2836-0
Verlag: Springer Netherland
Format: PDF
Kopierschutz: 1 - PDF Watermark



This is an important textbook on artificial intelligence that uses the unifying thread of search to bring together most of the major techniques used in symbolic artificial intelligence. The authors, aware of the pitfalls of being too general or too academic, have taken a practical approach in that they include program code to illustrate their ideas. Furthermore, code is offered in both POP-11 and Prolog, thereby giving a dual perspective, highlighting the merits of these languages.
Each chapter covers one technique and divides up into three sections:
  • a section which introduces the technique (and its usual applications) andsuggests how it can be understood as a variant/generalisation of search;
  • a section which developed a `low'-level (POP-11) implementation;
  • a section which develops a high-level (Prolog) implementation of the technique.
The authors also include useful notes on alternative treatments to the material, further reading and exercises.
As a practical book it will be welcomed by a wide audience including, those already experienced in AI, students with some background in programming who are taking an introductory course in AI, and lecturers looking for a precise, professional and practical text book to use in their AI courses.
About the authors:
has a BA in Economics, an Sc in Computer Science and a DPhil in Artificial Intelligence. Formerly a lecturer in the Department of AI at the University of Edinburgh, he is now a lecturer in AI in the School of Cognitive and Computing Sciences at the University of Sussex.
has a BSc in Physics and a PhD in Artificial Intelligence. Previously a lecturer in the Department of Computing Science at the University of Aberdeen he is currently Professor of Artificial Intelligence, also in the School of Cognitive and Computing Sciences, University of Sussex.
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Zielgruppe


Research

Weitere Infos & Material


1. Search-Related Techniques in AI. 2. Simple State Space Search. 3. State-Space Search. 4. Heuristic State-Space Search. 5. Heuristc Search of Game Trees. 6. Problem Reduction (AND/OR-Tree Search). 7. Planning (Microworld Search). 8. Parsing (Search as Analysis). 9. Expert Systems (Probabilistic Search). 10. Concept Learning (Extension-Generating Search). 11. Prolog (Search as Computation). 12. References. Introduction to POP-11 Programming. Index.



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