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by Burak Kanber, Lee Jacobson
Genetic Algorithms in Java Basics
Cover
Title
Copyright
Contents at a Glance
Contents
About the Authors
About the Technical Reviewers
Preface
Chapter 1: Introduction
What is Artificial Intelligence?
Biologically Analogies
History of Evolutionary Computation
The Advantage of Evolutionary Computation
Biological Evolution
An Example of Biological Evolution
Basic Terminology
Terms
Search Spaces
Fitness Landscapes
Local Optimums
Parameters
Mutation Rate
Population Size
Crossover Rate
Genetic Representations
Termination
The Search Process
CITATIONS
Chapter 2:Implementation of a Basic Genetic Algorithm
Pre-Implementation
Pseudo Code for a Basic Genetic Algorithm
About the Code Examples in this Book
Basic Implementation
The Problem
Parameters
Initialization
Evaluation
Termination Check
Crossover
Elitism
Mutation
Execution
Summary
Chapter 3: Robotic Controllers
Introduction
The Problem
Implementation
Before You Start
Encoding
Initialization
Evaluation
Termination Check
Selection Method and Crossover
Execution
Summary
Exercises
Chapter 4: Traveling Salesman
Introduction
The Problem
Implementation
Before You Start
Encoding
Initialization
Evaluation
Termination Check
Crossover
Mutation
Execution
Summary
Exercises
Chapter 5: Class Scheduling
Introduction
The Problem
Implementation
Before You Start
Encoding
Initialization
The Executive Class
Evaluation
Termination
Mutation
Execution
Analysis and Refinement
Exercises
Summary
Chapter 6: Optimization
Adaptive Genetic Algorithms
Implementation
Exercises
Multi-Heuristics
Implementation
Exercises
Performance Improvements
Fitness Function Design
Parallel Processing
Fitness Value Hashing
Encoding
Mutation and Crossover Methods
Summary
Index
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Copyright
Genetic Algorithms in Java Basics
Lee Jacobson
Burak Kanber
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