Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/70655
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Type: | Conference paper |
Title: | Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics |
Author: | Durrett, G. Neumann, F. O'Reilly, U. |
Citation: | Proceeding: FOGA '11: Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms, 2011: pp.69-80 |
Publisher: | ACM Press |
Publisher Place: | New York |
Issue Date: | 2011 |
ISBN: | 9781450306331 |
Conference Name: | ACM SIGEVO Workshop on Foundations of Genetic Algorithms (11th : 2011 : Schwarzenberg, Austria) |
Statement of Responsibility: | Greg Durrett, Frank Neumann, Una-May O’Reilly |
Abstract: | Analyzing the computational complexity of evolutionary algorithms (EAs) for binary search spaces has significantly informed our understanding of EAs in general. With this paper, we start the computational complexity analysis of genetic programming (GP). We set up several simplified GP algorithms and analyze them on two separable model problems, ORDER and MAJORITY, each of which captures a relevant facet of typical GP problems. Both analyses give first rigorous insights into aspects of GP design, highlighting in particular the impact of accepting or rejecting neutral moves and the importance of a local mutation operator. |
Keywords: | Algorithms Theory |
Rights: | Copyright 2011 ACM |
DOI: | 10.1145/1967654.1967661 |
Description (link): | http://www.sigevo.org/foga-2011/ |
Published version: | http://dx.doi.org/10.1145/1967654.1967661 |
Appears in Collections: | Aurora harvest 5 Computer Science publications |
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RA_hdl_70655.pdf Restricted Access | Restricted Access | 501.57 kB | Adobe PDF | View/Open |
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