DocumentCode :
2691576
Title :
Measuring complexity by measuring structure and organization
Author :
Hornby, Gregory S.
Author_Institution :
U.C. Santa Cruz, Moffett Field
fYear :
2007
fDate :
25-28 Sept. 2007
Firstpage :
2017
Lastpage :
2024
Abstract :
Necessary for furthering the development of more powerful evolutionary design systems, capable of scaling to evolving more sophisticated and complex artifacts, is the ability to meaningfully and objectively compare these systems by applying complexity measures to the artifacts they evolve. Previously we have proposed measures of modularity, reuse and hierarchy (MR&H), here we compare these measures to ones from the fields of complexity, systems engineering and computer programming. In addition, we propose several ways of combining the MR&H measures into a single measure of structure and organization. We compare all of these measures empirically as well as on three sample objects and find that the best measures of complexity are two of the proposed measures of structure and organization.
Keywords :
computational complexity; evolutionary computation; evolutionary computation; evolutionary design systems; measuring complexity; measuring organization; measuring structure; Biology computing; Cells (biology); Computational biology; Design engineering; Embryo; Programming; Scalability; Size measurement; Systems engineering and theory; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
Type :
conf
DOI :
10.1109/CEC.2007.4424721
Filename :
4424721
Link To Document :
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