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Function discovery system by evolutionary computation using search accumulation
Author(s) -
Saito Mitsutoshi,
Serikawa Seiichi
Publication year - 2010
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.10098
Subject(s) - function (biology) , computer science , search algorithm , algorithm , data mining , mathematics , biology , evolutionary biology
Recently, a system using bug‐type artificial life was proposed for function discovery, and has been improved further. This system is an extended model of GA and GP. However, when the observation data is very complicated, the function is occasionally not obtained. A new concept is now introduced so that the function search can be applied to complicated observation data. The function search by the S‐System is performed two or more times. This is termed search accumulation. To confirm the validity of search accumulation, the Himmelblau function, the valley function, and equal loudness level contours (ISO 226) are used as observation data. Since the distributions of the data are complicated, it is difficult to express them as an approximation function. By the use of the search accumulation strategy, a function that is in good agreement with the distribution can be successfully obtained. Thus, the validity of this strategy is confirmed. Search accumulation is also applicable to GP. © 2010 Wiley Periodicals, Inc. Electron Comm Jpn, 93(10): 53–62, 2010; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/ecj.10098 3