Measuring complexity by measuring structure and organization

被引:4
|
作者
Hornby, Gregory S. [1 ]
机构
[1] UC Santa Cruz, Moffett Field, CA USA
关键词
D O I
10.1109/CEC.2007.4424721
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
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页码:2017 / 2024
页数:8
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