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Book Excerpts:
This book provides the theory of many useful techniques for AI programming. Readers should find this a fun book to work through. In the style of a "cookbook", the chapters in this book can be studied in any order. Each chapter follows the same pattern: a motivation for learning a technique, some theory for the technique, and a Java example program that readers can experiment with.
Subjects discussed in this book include search algorithms, natural language processing, expert systems, genetic algorithms, neural networks, machine learning, statistical natural language processing and spam email detection using Bayesian rules.
There are relatively few source code listings in this book, but complete example programs that are discussed in the text should have been included in the same ZIP file that contained this web book. Should reader find this this web book without the examples, she can download an up to date version of the book and examples on the Open Content page of
In order to discuss some of the example code in this book, the author used Unified Modeling Language (UML) class diagrams. These diagrams were created using the TogetherJ modeling tool.
Intended Audience:
This book was written for both professional programmers and home hobbyists who already know how to program in Java and who want to learn practical AI programming techniques.
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