Abstract

One of the obstacles to Evolutionary Algorithms (EAs) fulfilling their promise as easy to use general-purpose problem solvers, is the difficulty of correctly configuring them for specific problems such as to obtain satisfactory performance. Having a mechanism for automatically configuring parameters and operators of every stage of the evolutionary life-cycle would give EAs a more widely spread popularity in the non-expert community. This paper investigates automatic configuration of one of the stages of the evolutionary life-cycle, the parent selection, via a new concept of semi-autonomous parent selection, where mate selection operators are encoded and evolved as in Genetic Programming. We compare the performance of the EA with semi-autonomous parent selection to that of a manually configured EA on three common test problems to determine the “price” we pay for user-friendliness.

Meeting Name

2007 IEEE Congress on Evolutionary Computation (2007: Sep. 25-28, Singapore)

Department(s)

Computer Science

Keywords and Phrases

Automatic Configuration; Evolutionary Algorithms; Genetic Programming

International Standard Book Number (ISBN)

978-1-4244-1339-3

International Standard Serial Number (ISSN)

1089-778X

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2007 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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