A Field Guide to Genetic Programming

A Field Guide to Genetic Programming

A Field Guide to Genetic Programming
by R. Poli, W. B. Langdon, N. F. McPhee

Publisher: Lulu.com 2008
ISBN/ASIN: 1409200736
ISBN-13: 9781409200734
Number of pages: 252

Genetic programming 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 a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP.

Home page url

Download or read it online here:
Download link
(3.8MB, PDF)

Similar books

Evolutionary AlgorithmsEvolutionary Algorithms
by Eisuke Kita - InTech
Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on.
Genetic Programming: New Approaches and Successful ApplicationsGenetic Programming: New Approaches and Successful Applications
by Sebastian Ventura (ed.) - 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 ...
Advances in Evolutionary AlgorithmsAdvances in Evolutionary Algorithms
by Witold Kosinski - InTech
With the recent trends towards massive data sets and significant computational power, evolutionary computation is becoming much more relevant to practice. The book presents recent improvements, ideas and concepts in a part of a huge EA field.
Global Optimization Algorithms: Theory and ApplicationGlobal Optimization Algorithms: Theory and Application
by Thomas Weise
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.