AI Application Programming
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...
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The purpose of this book is to demystify the techniques associated with the field of artificial intelligence. It will cover a wide variety of techniques currently defined as "AI" and show how they can be useful in practical, everyday applications. Many books on artificial intelligence provide tutorials for AI methods, but their applications are restricted to toy problems that have little relevance in the real world. AI Application Programming covers both the theory and the practical applications to teach developers how to apply AI techniques in their own designs. The book is split by AI subfields (statistical methods, symbolic methods, etc.) to further refine the methods and applications for the reader. Each chapter covers both the theory of the algorithm or the technique under discussion and follows with a practical application of the technique with a detailed discussion of the source code. Key Features: Covers cutting edge AI concepts such as neural networks, genetic algorithms, intelligent agents, rules-based systems, ant algorithms, fuzzy logic, unsupervised learning algorithms, and more Provides practical applications including a personalization application, a rules-based reasoning system, a character trainer for game AI, a Web-based news agent, a fuzzy battery charge controller, a genetic code generator, artificial life simulation, and others Includes a CD-ROM with complete source code for the applications ON the CD The CD-ROM contains a number of useful applications and source code that demonstrate the properties of AI algorithmic techniques and methods(WIN/Linux). APPLICATIONS Simulated Annealing Adaptive Resonance Theory Ant Algorithms Backpropagation Algorithm Genetic Algorithms / Genetic Programming Artificial Life / Evolving Neural Networks Expert Systems Fuzzy Logic Hidden Markov Models Intelligent Agents SYSTEM REQUIREMENTS: Applications on this CD-ROM require a PC with Windows 95, 98, 2000, Me, or XP using the Cygwin UNIX environment (freely downloadable); or Linux (Red Hat 6.1 or later, or comparable Linux distribution); 486 or higher CPU; 64MB RAM; 60MB disk space; CD-ROM drive; Internet access and Web browser (for the WebAgent example).
History of AI Simulated Annealing Adaptive Resonance Theory Ant Algorithms Backpropagation Neural Networks Genetic Algorithms / Genetic Programming Neural Network Evolution Rules-Based Systems Fuzzy Logic Hidden Markov Models Intelligent Agents AI Today About the CD
\ From Barnes & NobleThe Barnes & Noble Review\ Slowly, 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.\ \ \
