Adapting the Covariance Matrix in Evolution Strategies

Silja Meyer-Nieberg, Erik Kropat


Evolution strategies belong to the best performing modern natural computing methods for continuous optimization. This paper addresses the covariance matrix adaptation which is central to the algorithm. Nearly all approaches so far consider the sample covariance as one of the main factors for the adaptation. However, as known from modern statistics, this estimate may be of poor quality in many cases. Unfortunately, these cases are encountered often in practical applications. This paper explores the use of different previously unexplored estimates.


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Paper Citation

in Harvard Style

Meyer-Nieberg S. and Kropat E. (2014). Adapting the Covariance Matrix in Evolution Strategies . In Proceedings of the 3rd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-017-8, pages 89-99. DOI: 10.5220/0004832300890099

in Bibtex Style

author={Silja Meyer-Nieberg and Erik Kropat},
title={Adapting the Covariance Matrix in Evolution Strategies},
booktitle={Proceedings of the 3rd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},

in EndNote Style

JO - Proceedings of the 3rd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Adapting the Covariance Matrix in Evolution Strategies
SN - 978-989-758-017-8
AU - Meyer-Nieberg S.
AU - Kropat E.
PY - 2014
SP - 89
EP - 99
DO - 10.5220/0004832300890099