Practical Artificial Intelligence Programming in Java
Author:
Mark Watson
Year: 2005
Publisher: GNU Free Documentation License
Content URL: Link To Content
About Practical Artificial Intelligence Programming in Java:
Excerpts from book:
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. I have tried to make this a fun book to work through. In the style of a “cook book”, 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 you can experiment with.
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.
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. I have tried to make this a fun book to work through. In the style of a “cook book”, 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 you can experiment with.
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.