GENETIC ALGORITHMS IN SEARCH, OPTIMIZATION AND MACHINE LEARNING 1ST EDITION

Book Details

• Author: Goldberg

• Binding: Paperback

• Number of Pages: 200

• Release Date: 01-12-2008

• ISBN: 9788131709931

• Package Dimensions: 9.4 x 7.2 x 0.7 inches

• Languages: English

About the Book

"Genetic Algorithms" by Goldberg introduces the fundamental concepts of genetic algorithms (GAs), which are search algorithms inspired by the process of natural selection and genetics. This text provides a comprehensive understanding of how these powerful algorithms can be used to solve optimization and search problems in diverse fields.

At its core, genetic algorithms simulate the natural evolutionary process, where solutions evolve over successive generations through selection, crossover, and mutation. The book explores both the theory behind genetic algorithms and their practical applications, providing a balanced view for both students and professionals seeking to understand the mechanics of GAs.

Goldberg covers the following key topics:

• Theory of Genetic Algorithms: The principles that drive the process of evolution and their translation into search algorithms.

• Operation of Genetic Algorithms: How genetic algorithms are implemented and function within computational frameworks.

• Applications: The wide range of practical problems where genetic algorithms can be applied, from optimization problems to complex machine learning tasks.

With clear explanations and practical insights, this book serves as an excellent introduction to the world of genetic algorithms for those looking to apply evolutionary computation in solving real-world problems.

Whether you are a student studying computer science, a researcher in artificial intelligence, or a professional in fields that involve optimization and search algorithms, this book will equip you with a solid foundation in genetic algorithms.