Hardcover in dust jacket. Clean text - NO writing, NO highlighting to text. Book is Very good. Dus tjacket has a 3.5" closed tear to head of front panel near spine hinge. Light surface wear. A Very good/Good reading copy. Oversized.� Clean text -- NO writing, NO highlighting to text.�PLEASE NOTE: Domestic US media (standard) US orders ONLY.� NO international orders.

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Bibliographic Details

Title: Genetic Programming II: Automatic Discovery of Reusable Programs (Complex Adaptive Systems)
Publisher: The MIT Press
Publication Date: 1994
Language: English
ISBN 10: 0262111896
ISBN 13: 9780262111898
Binding: Hardcover
Condition: Good
Dust Jacket Condition: Dust Jacket Included

About this title

Synopsis

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.

About the Author

John R. Koza is Consulting Professor in the Computer Science Department at Stanford University.

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