Features
- Cover Type: Hard Cover with 498 pages
- Published by: Infinity Science Press
- Edition: 1st Edition September 30, 2007
- Written in: English
- ISBN 10 Number: 0977858235
- ISBN 13 Number: 978-0977858231
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Book Dimensions:
9.1 x 7.2 x 1.2 inches
- Weighs: 1.8 pounds
Product Description
This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed. This sensor / algorithm / effecter approach grounds the algorithms with an environment, helps students and AI practitioners to better understand them, and subsequently, how to apply them. The book has numerous up to date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more. A CD-ROM with simulations, code, and figures accompanies the book. *Features *Covers not only AI theory, but modern applications e.g., game programming, machine learning, swarming, artificial immune systems, genetic algorithms, pattern recognition, numerical optimization, data mining, and more *Discusses the various computer languages of AI from LISP to JAVA and Python *Includes a CD-ROM with 100MB of simulations, code, and fi gures *Table of Contents 1. Introduction. 2. Search. 3. Games. 4. Logic. 5. Planning. 6. Knowledge Representation. 7. Machine Learning. 8. Probabilistic Reasoning. 9. Stochastic Search. 10. Neural Networks. 11. Intelligent Agents. 12. Hybrid Models. 13. Languages of AI.
About The Author
M. Tim Jones is an author of numerous articles on a variety of technical subjects. He is also the author of the bestselling, AI Applications 2/E.
Reader ReviewsThe book points out that AI is celebrating its 50th anniversary. Appropriately, then, the text surveys the many ideas in AI. Neural networks is one such topic. In the 80s, this was perhaps considered to be outside AI, but the tenor of the narrative is that it has since become subsumed squarely inside AI, as a powerful technique. Along these lines, space is given to showing how some models are inspired by biology. Including the idea of evolutionary computation and genetic algorithms. The use of evolution as a guiding metaphor can sometimes be fruitful in looking for optimal solutions to hard problems. Robotics is also keenly discussed. There is an entire taxonomy of hardware types, and the abilities increase every year. At the software level, cellular automata are popular. From these, studies of artificial life are summarised. Surprisingly, there is no mention of Stephen Wolfram. He made some key contributions to studies of cellular automata, and his omission from the text is puzzling.
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