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Evolution of numeric constants in Genetic Programming
- 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 |
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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. |
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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. |