creators_name: Whitacre, James M
creators_name: Pham, Tuan Q.
creators_name: Sarker, Ruhul A.
type: confpaper
datestamp: 2009-07-06 09:42:49
lastmod: 2011-03-11 08:57:23
metadata_visibility: show
title: Use of Statistical Outlier Detection Method in Adaptive
Evolutionary Algorithms
ispublished: pub
subjects: comp-sci-art-intel
full_text_status: public
keywords: Evolutionary Algorithm, Genetic Algorithm, Feedback
Adaptation
abstract: In this paper, the issue of adapting probabilities for Evolutionary Algorithm (EA) search operators is revisited. A framework is devised for distinguishing between measurements of performance and the interpretation of those measurements for purposes of adaptation. Several examples of measurements and statistical interpretations are provided. Probability value adaptation is tested using an EA with 10 search operators against 10 test problems with results indicating that both the type of measurement and its statistical interpretation play significant roles in EA performance. We also find that selecting operators based on the prevalence of outliers rather than on average performance is able to provide considerable improvements to
adaptive methods and soundly outperforms the non-adaptive
case.
date: 2006-07-08
date_type: published
refereed: TRUE
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citation:   Whitacre, Dr James M and Pham, Dr Tuan Q. and Sarker, Dr Ruhul A.  (2006) Use of Statistical Outlier Detection Method in Adaptive Evolutionary Algorithms.  [Conference Paper]     
document_url: http://cogprints.org/6579/1/Statistical_interpretation_of_adaptive_performance_in_genetic_algorithms-whitacre.pdf