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Sanchez, Ernesto; Schillaci, Massimiliano; Squillero, Giovanni - Evolutionary Optimization: the Gp Toolkit - 9781489993687 - V9781489993687
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Evolutionary Optimization: the Gp Toolkit

€ 132.46
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Description for Evolutionary Optimization: the Gp Toolkit Paperback. This text begins with an overview of the most popular techniques of evolutionary computation followed by a discussion of the theoretical and practical aspects of muGP. It includes several detailed examples with actual results. Num Pages: 191 pages, biography. BIC Classification: UB; UGC; UYQ. Category: (G) General (US: Trade). Dimension: 235 x 155 x 11. Weight in Grams: 308.

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 μGP (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.

For a practitioner, μGP 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 ... Read more

For an evolutionary computation researcher, μGP may be regarded as a platform where new operators and strategies can be easily tested.

MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/

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Product Details

Format
Paperback
Publication date
2014
Publisher
Springer-Verlag New York Inc. United States
Number of pages
191
Condition
New
Number of Pages
178
Place of Publication
New York, United States
ISBN
9781489993687
SKU
V9781489993687
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Evolutionary Optimization: the Gp Toolkit
From the reviews: “The text is a handbook for µGP. It is aimed at providing the reader with all of the information required for proficient use of the tool. … At the end of the book, a chapter presents a number of examples and applications. … the book meets its main objective of being a reference for the µGP ... Read more

Goodreads reviews for Evolutionary Optimization: the Gp Toolkit


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