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Evolutionary Optimization: the uGP toolkit - Loukas Grafakos
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Evolutionary Optimization: the uGP toolkit - nouveau livre

ISBN: 9780387094267

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 t… Plus…

No. 9780387094267. Frais d'envoiInstock, Despatched same working day before 3pm, zzgl. Versandkosten., Livraison non-comprise
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Evolutionary Optimization: the uGP toolkit - Carol Parikh
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Evolutionary Optimization: the uGP toolkit - nouveau livre

ISBN: 9780387094267

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 t… Plus…

No. 9780387094267. Frais d'envoiInstock, Despatched same working day before 3pm, zzgl. Versandkosten., Livraison non-comprise
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Evolutionary Optimization: the µGP toolkit - Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero
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Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero:
Evolutionary Optimization: the µGP toolkit - Première édition

2011

ISBN: 9780387094267

The UGP Toolkit, eBooks, eBook Download (PDF), Auflage, [PU: Springer-Verlag], [ED: 1], Springer-Verlag, 2011

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Evolutionary Optimization: the µGP toolkit - Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero
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Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero:
Evolutionary Optimization: the µGP toolkit - nouveau livre

2011, ISBN: 9780387094267

eBooks, eBook Download (PDF), 2011, [PU: Springer US], Springer US, 2011

Frais d'envoiDownload sofort lieferbar. (EUR 0.00)
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Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero:
Evolutionary Optimization: the µGP toolkit - nouveau livre

2011, ISBN: 9780387094267

2011, eBook Download (PDF), eBooks, [PU: Springer US]

Frais d'envoiDownload sofort lieferbar, , Versandkostenfrei innerhalb der BRD. (EUR 0.00)

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EAN (ISBN-13): 9780387094267
ISBN (ISBN-10): 0387094261
Date de parution: 2011
Editeur: Springer-Verlag
178 Pages
Langue: eng/Englisch

Livre dans la base de données depuis 2009-06-10T03:42:25+02:00 (Zurich)
Page de détail modifiée en dernier sur 2023-06-14T12:44:41+02:00 (Zurich)
ISBN/EAN: 9780387094267

ISBN - Autres types d'écriture:
0-387-09426-1, 978-0-387-09426-7
Autres types d'écriture et termes associés:
Auteur du livre: sanchez, massimi, pierre tan


Données de l'éditeur

Auteur: Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero
Titre: Evolutionary Optimization: the µGP toolkit
Editeur: Springer; Springer US
178 Pages
Date de parution: 2011-04-01
New York; NY; US
Imprimé / Fabriqué en
Langue: Anglais
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XIII, 178 p.

EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Evolutionary Optimization; Genetic Programming; Graph-based representation; Industrial Problems; MicroGP; Problem Complexity; Real-world Applications; Turing-complete; evolutionary algorithm; evolutionary computation; B; Artificial Intelligence; Computer Applications; Computer-Aided Engineering (CAD, CAE) and Design; Artificial Intelligence; Computer and Information Systems Applications; Computer-Aided Engineering (CAD, CAE) and Design; Computer Science; Angewandte Informatik; Computer-Aided Design (CAD); BB

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 communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.

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/

Evolutionary computation.- Why yet another one evolutionary optimizer?.- The μGP architecture.- Advanced features.- Performing an evolutionary run.- Command line syntax.- Syntax of the settings file.- Syntax of the population parameters file.- Syntax of the external constraints file.- Writing a compliant evaluator.- Implementation details.- Examples and applications.- Argument and option synopsis.- External constraints synopsis.- Index.- References

Describes an award-winning evolutionary algorithm used for solving practical problems in industry

Provides a practical guide on using the µGP, a set of examples to clarify the available choices and advice against common errors and misconceptions

Offers practical knowledge about applying various evolutionary schemes using the toolkit, and a set of useful rules of thumb for tuning all toolkit capabilities

Includes supplementary material: sn.pub/extras



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