Authors: M. Tim Jones, Jones
ISBN-13: 9781584504214, ISBN-10: 1584504218
Publisher: Cengage Learning
Date Published: June 2005
Edition: Book and CD
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.
- 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).
- 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
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).
Table of Contents
|History of AI|
|Adaptive Resonance Theory|
|Backpropagation Neural Networks|
|Genetic Algorithms / Genetic Programming|
|Neural Network Evolution|
|Hidden Markov Models|
|About the CD|