Practical Artificial Intelligence Programming in Java

Book Description

This book uses both best of breed open source software and the author's own libraries to introduce the reader to Artificial Intelligence (AI) technologies like genetic algorithms, neural networks, expert systems, machine learning, and statistical natural language processing (NLP).

Table of contents

• Introduction
• Other JVM Languages
• Why is a PDF Version of this Book Available Free on the Web?
• Book Software
• Use of Java Generics and Native Types
• Notes on Java Coding Styles Used in this Book
• Book Summary
• Representation of Search State Space and Search Operators
• Finding Paths in Mazes
• Finding Paths in Graphs
• Adding Heuristics to Breadth First Search
• Search and Game Playing
• Alpha-Beta Search
• A Java Framework for Search and Game Playing
• Tic-Tac-Toe Using the Alpha-Beta Search Algorithm
• Chess Using the Alpha-Beta Search Algorithm
• Logic
• History of Logic
• Examples of Different Logic Types
• Running PowerLoom Interactively
• Using the PowerLoom APIs in Java Programs
• Suggestions for Further Study
• Relational Database Model Has Problems Dealing with Rapidly Changing Data Requirements
• RDF: The Universal Data Format
• Extending RDF with RDF Schema
• The SPARQL Query Language
• Using Sesame
• OWL: The Web Ontology Language
• Knowledge Representation and REST
• Material for Further Study
• Expert Systems
• Production Systems
• The Drools Rules Language
• Using Drools in Java Applications
• Example Drools Expert System: Blocks World
• POJO Object Models for Blocks World Example
• Drools Rules for Blocks World Example
• Java Code for Blocks World Example
• Example Drools Expert System: Help Desk System
• Object Models for an Example Help Desk
• Drools Rules for an Example Help Desk
• Java Code for an Example Help Desk
• Notes on the Craft of Building Expert Systems
• Genetic Algorithms
• Theory
• Java Library for Genetic Algorithms
• Finding the Maximum Value of a Function
• Neural Networks
• Hopfield Neural Networks
• Java Classes for Hopfield Neural Networks
• Testing the Hopfield Neural Network Class
• Back Propagation Neural Networks
• A Java Class Library for Back Propagation
• Adding Momentum to Speed Up Back-Prop Training
• Machine Learning with Weka
• Using Weka’s Interactive GUI Application
• Interactive Command Line Use of Weka
• Embedding Weka in a Java Application
• Suggestions for Further Study
• Statistical Natural Language Processing
• Tokenizing, Stemming, and Part of Speech Tagging Text
• Named Entity Extraction From Text
• Using the WordNet Linguistic Database
• Tutorial on WordNet
• Example Use of the JAWS WordNet Library
• Suggested Project: Using a Part of Speech Tagger to Use
• the Correct WordNet Synonyms
• Suggested Project: Using WordNet Synonyms to Improve
• Document Clustering
• Automatically Assigning Tags to Text
• Text Clustering
• Spelling Correction
• GNU ASpell Library and Jazzy
• Peter Norvig’s Spelling Algorithm
• Extending the Norvig Algorithm by Using Word Pair Statistics
• Hidden Markov Models
• Training Hidden Markov Models
• Using the Trained Markov Model to Tag Text
• Information Gathering
• Open Calais
• Information Discovery in Relational Databases
• Creating a Test Derby Database Using the CIA World FactBook and Data on US States
• Using the JDBC Meta Data APIs
• Using the Meta Data APIs to Discern Entity Relationships
• Down to the Bare Metal: In-Memory Index and Search
• Indexing and Search Using Embedded Lucene
• Indexing and Search with Nutch Clients
• Nutch Server Fast Start Setup
• Using the Nutch OpenSearch Web APIs

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