Logo

Advances in Genetic Programming, Vol. 3

Large book cover: Advances in Genetic Programming, Vol. 3

Advances in Genetic Programming, Vol. 3
by

Publisher: The MIT Press
ISBN/ASIN: 0262194236
ISBN-13: 9780262194235
Number of pages: 488

Description:
Genetic programming is a form of evolutionary computation that evolves programs and program-like executable structures for developing reliable time- and cost-effective applications. This third volume of Advances in Genetic Programming highlights many of the recent technical advances in this increasingly popular field.

Home page url

Download or read it online for free here:
Download link
(multiple PDF files)

Similar books

Book cover: Genetic Programming: New Approaches and Successful ApplicationsGenetic Programming: New Approaches and Successful Applications
by - InTech
Genetic programming (GP) is a branch of Evolutionary Computing that aims the automatic discovery of programs to solve a given problem. Since its appearance, in the earliest nineties, GP has become one of the most promising paradigms ...
(4018 views)
Book cover: A Field Guide to Genetic ProgrammingA Field Guide to Genetic Programming
by - Lulu.com
This book is an introduction to genetic programming GP is a systematic method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. GP has generated lots of results and applications.
(9812 views)
Book cover: Genetic Algorithms and Evolutionary ComputationGenetic Algorithms and Evolutionary Computation
by - The TalkOrigins Archive
Creationists argue that evolutionary processes cannot create new information, or that evolution has no practical benefits. This article disproves those claims by describing the explosive growth and widespread applications of genetic algorithms.
(3930 views)
Book cover: Global Optimization Algorithms: Theory and ApplicationGlobal Optimization Algorithms: Theory and Application
by
The book on global optimization algorithms - methods to find optimal solutions for given problems. It focuses on evolutionary algorithms, genetic algorithms, genetic programming, learning classifier systems, evolution strategy, etc.
(7711 views)