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<oembed><version>1.0</version><provider_name>Arbeitsgemeinschaft der Universit&#xE4;tsverlage</provider_name><provider_url>https://universitaetsverlage.eu</provider_url><author_name>XMLRPC</author_name><author_url>https://universitaetsverlage.eu/author/xmlrpc/</author_url><title>Evolutionary computation in stochastic environments - Arbeitsgemeinschaft der Universit&#xE4;tsverlage</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content"&gt;&lt;a href="https://universitaetsverlage.eu/bucher-e-books/titel/evolutionary-computation-in-stochastic-environments/"&gt;Evolutionary computation in stochastic environments&lt;/a&gt;&lt;/blockquote&gt;
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&lt;/script&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://universitaetsverlage.eu/bucher-e-books/titel/evolutionary-computation-in-stochastic-environments/embed/" width="600" height="338" title="&#x201E;Evolutionary computation in stochastic environments&#x201C; &#x2014; Arbeitsgemeinschaft der Universit&#xE4;tsverlage" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;</html><thumbnail_url>https://universitaetsverlage.eu/wp-content/uploads/asolmerce/image-9783866441286.jpg</thumbnail_url><thumbnail_width>452</thumbnail_width><thumbnail_height>640</thumbnail_height><description>This book develops efficient methods for the application of Evolutionary Algorithms on stochastic problems. To achieve this, procedures for statistical selection are systematically analyzed with respect to different measures and significantly improved. It is shown how to adapt one of the best procedures for the needs of Evolutionary Algorithms and Evolutionary operators for efficient implementation in stochastic environments are identified.</description></oembed>
