- 1 Introduction
- 2 Table of Contents
- 22.214.171.124 Chapter No 1 Introduction
- 126.96.36.199 Chapter No 2 Search
- 188.8.131.52 Chapter No 3 Reasoning
- 184.108.40.206 Chapter No 4 Semantic Web
- 220.127.116.11 Chapter No 5 Expert Systems
- 18.104.22.168 Chapter No 6 Genetic Algorithms
- 22.214.171.124 Chapter No 7 Neural Networks
- 126.96.36.199 Chapter No 8 Machine Learning with Weka
- 188.8.131.52 Chapter No 9 Statistical Natural Language Processing
- 184.108.40.206 Chapter No 10 Information Gathering
- 2.1 Related Posts:
There are many fine books on Artificial Intelligence (AI) and good tutorials and software on the web. This book is intended for professional programmers who either already have an interest in AI or need to use specific AI technologies at work. The material is not intended as a complete reference for AI theory. Instead, I provide enough theoretical background to understand the example programs and to provide a launching point if you want or need to delve deeper into any of the topics covered.
The Java language and JVM platform are very widely used so that techniques that you learn can be broadly useful. There are other JVM languages like JRuby, Clojure, Jython, and Scala that can use existing Java classes. While the examples in this book are written in Java you should have little trouble using my Java example classes and the open source libraries with these alternative JVM languages.