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More About This Textbook
Overview
In the second edition of this bestseller, the author continues to demystify the techniques associated with the field of artificial intelligence. It covers a wide variety of techniques currently defined as "AI" and shows how they can be useful in practical, everyday applications. AI Application Programming covers both the theory and the practical applications to teach developers how to apply AI techniques in their own designs. Each chapter covers both the theory of the algorithm or the technique under discussion followed by a practical application of the technique with a detailed discussion of the source code.
Editorial Reviews
From Barnes & Noble
The Barnes & Noble ReviewSlowly, painfully, inexorably, AI gets more and more useful. AI techniques are now showing up in everything from recommendation systems to news agents, sensors to speech recognition -- and, increasingly, in mainstream business and technical software, too. This book takes AI out of the traditional “AI ghetto,” introducing its algorithms and techniques to “typical” programmers who can now derive great value from them.
M. Tim Jones covers pretty much every useful category of AI programming: neural networks, expert systems, fuzzy logic, genetic algorithms, rules-based systems, and more. While a few of the sample applications are theoretical, most are very practical, and drawn straight from the real world.
For example, Jones introduces Adaptive Resonance Theory (ART) in the context of e-commerce recommender systems (“you liked ‘Book A,’ you’ll probably like ‘Book Q,’ too”). There’s a chapter on the recently developed “ant algorithms,” which attempt to mimic the techniques blind ants use to navigate complex environments and get back home safely. (Exceptionally useful for solving highly dynamic problems, such as routing in rapidly changing networks.)
Jones shows how neural networks can be used in creating intelligent game behaviors; how intelligent agents are being used in today’s content and news filtering systems; how artificial life works; and how hidden Markov models can be used to fabricate text that resembles existing literary works. (Maybe they’ll never generate new Shakespeare, but Tom Clancy? Definitely possible.)
All the source code’s on CD-ROM. It’s tested to run under Red Hat Linux (6.1 and up) or any recent version of Windows running the free Cygwin Unix emulator. Bill Camarda
Bill Camarda is a consultant, writer, and web/multimedia content developer. His 15 books include Special Edition Using Word 2000 and Upgrading & Fixing Networks for Dummies, Second Edition.
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Meet the Author
M. Tim Jones is an embedded software architect and the author of numerous books, including AI Application Programming, Second Edition (Charles River Media), BSD Sockets Programming from a Multilanguage Perspective (Charles River Media), Artifi cial Intelligence: A Systems Approach, and many articles on a variety of technical subjects. His engineering background ranges from the development of kernels for geosynchronous spacecraft to embedded systems architecture and networking protocols development. Tim is a consultant engineer for Emulex Corp. in Longmont, Colorado.
Table of Contents
History of AI What is AI? Strong and Weak AI The Result of AI AIs Modern Timeline Branches of AI Key Researchers Philosophical, Moral, and Social Issues Structure of this Book 2 Pathfinding and the A-Star Algorithm 3 Simulated Annealing 4 Particle Swarm Optimization 5 Introduction to Adaptive Resonance Theory (ART1) 6 Introduction to Classifier Systems 7 Ant Algorithms 8 Introduction to Neural Networks and the Backpropagation 9 Introduction to Reinforcement Learning 10 Introduction to Genetic Algorithms 11 Artificial Life 13 Introduction to Fuzzy Logic 14 Natural Language Processing 15 The Bigram Model 16 Agent-based Software 17 AI Today References Resources Appendix A Exercises and Problems Appendix B About the CD-ROM