<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0">
<channel>
<title><![CDATA[Comentarios al libro: EVOLUTIONARY OPTIMIZATION: THE Â?GP TOOLKIT]]></title>
<link><![CDATA[https://api.biblioeteca.com/biblioeteca.web/titulo/evolutionary-optimization%3A-the-agp-toolkit]]></link>
<description><![CDATA[This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled ?GP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers.<p>For a practitioner, ?GP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.<p>For an evolutionary computation researcher, ?GP may be regarded as a platform where new operators and strategies can be easily tested.<p>MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/]]></description>
<lastBuildDate>Sat, 06 Jun 2026 06:59:59 +0000</lastBuildDate>
<language>es</language>
<copyright>Copyright 2021 BiblioEteca Technologies SL</copyright>

</channel>
</rss>
