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Evolution of numeric constants in Genetic Programming

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Date Issued:
1997
Summary:
Genetic Programming is an evolutionary technique for searching through the space of S-expressions for programs that represent optimal or acceptable solutions to a given problem. Genetic Programming often has difficulty in finding the appropriate numeric constants to use in leaf nodes of the S-expressions. This thesis describes the use of local search algorithms to search for numeric constants that will improve the S-expressions found by Genetic Programming. Three methods, Multi-Dimensional Hill Climbing, Vector Hill Climbing, and Numeric Mutation are combined with Genetic Programming to create hybrid systems. The performance of these hybrid systems is analyzed and future directions for improving Genetic Programming with the use of hybrid systems are discussed.
Title: Evolution of numeric constants in Genetic Programming.
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Name(s): Fernandez, Thomas
Florida Atlantic University, Degree grantor
Evett, Matthew P., Thesis advisor
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1997
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 109 p.
Language(s): English
Summary: Genetic Programming is an evolutionary technique for searching through the space of S-expressions for programs that represent optimal or acceptable solutions to a given problem. Genetic Programming often has difficulty in finding the appropriate numeric constants to use in leaf nodes of the S-expressions. This thesis describes the use of local search algorithms to search for numeric constants that will improve the S-expressions found by Genetic Programming. Three methods, Multi-Dimensional Hill Climbing, Vector Hill Climbing, and Numeric Mutation are combined with Genetic Programming to create hybrid systems. The performance of these hybrid systems is analyzed and future directions for improving Genetic Programming with the use of hybrid systems are discussed.
Identifier: 9780591624946 (isbn), 15493 (digitool), FADT15493 (IID), fau:12257 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (M.S.)--Florida Atlantic University, 1997.
Subject(s): Genetic programming (Computer science)
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/15493
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.