Evaluating the CMA Evolution Strategy on Multimodal Test Functions
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Publisher
Springer Berlin Heidelberg
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http://link.springer.com/content/pdf/10.1007/978-3-540-30217-9_29.pdf
Reference9 articles.
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3. Lecture Notes in Computer Science;S.D. Müller,2002
4. Hansen, N., Müller, S.D., Koumoutsakos, P.: Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evol. Comput. 11, 1–18 (2003)
5. Kern, S., Müller, S.D., Hansen, N., Büche, D., Ocenasek, J., Koumoutsakos, P.: Learning probability distributions in continuous evolutionary algorithms – a comparative review. Natural Computing 3, 77–112 (2004)
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