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Genetic Programming II: Automatic Discovery of Reusable Programs (Complex Adaptive Systems)

Genetic Programming II: Automatic Discovery of Reusable Programs (Complex Adaptive Systems) Cover

 

Synopses & Reviews

Publisher Comments:

Genetic Programming II extends the results of John Koza's ground-breaking work on programming by means of natural selection, described in his first book, Genetic Programming. Using a hierarchical approach, Koza shows that complex problems can be solved by breaking them down into smaller, simpler problems using the recently developed technique of automatic function definition in the context of genetic programming.Where conventional techniques of machine learning and artificial intelligence fail to provide an effective means for automatically handling the process of decomposing complex problems into smaller subsets, reassembling the solutions to these subsets, and applying an overall solution to the original problem, automatic function definition enables genetic programming to define useful and reusable subroutines dynamically. Koza illustrates this new technique by showing how it solves (or approximately solves) a variety of problems in Boolean function learning, symbolic regression, control, pattern recognition, robotics, classification, and molecular biology.In each example, the problem is automatically decomposed into subproblems; the subproblems are automatically solved; and the solutions to the subproblems are automatically assembled into a solution to the original problem. Koza shows that leverage accrues because genetic programming with automatic function definition repeatedly uses the solutions to the subproblems in the assembly of the solution to the overall problem. Moreover, genetic programming with automatic function definition produces solutions that are simpler and smaller than the solution obtained without automatic function definition.

Book News Annotation:

Extends the results of the previous volume discussing programming by means of natural selection. Using a hierarchical approach, Koza explains that complex problems can be solved by breaking them down into smaller, simpler problems using the recently developed technique of automatic function definition.
Annotation c. Book News, Inc., Portland, OR (booknews.com)

Synopsis:

In each example, the problem is automatically decomposed into subproblems; the subproblems are automatically solved; and the solutions to the subproblems are automatically assembled into a solution to the original problem. Koza shows that leverage accrues because genetic programming with automatic function definition repeatedly uses the solutions to the subproblems in the assembly of the solution to the overall problem. Moreover, genetic programming with automatic function definition produces solutions that are simpler and smaller than the solution obtained without automatic function definition.

Description:

Includes bibliographical references (p. [719] and index.

Product Details

ISBN:
9780262111898
Subtitle:
Automatic Discovery of Reusable Programs
Author:
Koza, John R.
Publisher:
A Bradford Book
Location:
Cambridge, Mass. :
Subject:
General
Subject:
Programming - General
Subject:
Genetics
Subject:
Artificial Intelligence
Subject:
Genetic engineering
Subject:
Genetic programming (Computer science)
Subject:
Genetic programming
Subject:
Artificial Intelligence - General
Series:
Complex Adaptive Systems Genetic Programming II
Series Volume:
618
Publication Date:
19940517
Binding:
Hardback
Grade Level:
from 17
Language:
English
Illustrations:
Yes
Pages:
768
Dimensions:
10.2 x 7.2 x 1.7 in

Related Subjects

Computers and Internet » Artificial Intelligence » General
Science and Mathematics » Environmental Studies » Environment

Genetic Programming II: Automatic Discovery of Reusable Programs (Complex Adaptive Systems)
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Product details 768 pages Bradford Book - English 9780262111898 Reviews:
"Synopsis" by , In each example, the problem is automatically decomposed into subproblems; the subproblems are automatically solved; and the solutions to the subproblems are automatically assembled into a solution to the original problem. Koza shows that leverage accrues because genetic programming with automatic function definition repeatedly uses the solutions to the subproblems in the assembly of the solution to the overall problem. Moreover, genetic programming with automatic function definition produces solutions that are simpler and smaller than the solution obtained without automatic function definition.
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