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Sanchez, Ernesto:

Evolutionary Optimization: the GP toolkit The UGP Toolkit Ernesto Sanchez (u. a.) Buch Englisch 2011 - encadernada, livro de bolso

2011, ISBN: 9780387094250

[ED: Gebunden], [PU: Springer-Verlag GmbH], This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial… mais…

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Sanchez, Ernesto:

Evolutionary Optimization: the GP toolkit The UGP Toolkit Ernesto Sanchez (u. a.) Buch Englisch 2011 - encadernada, livro de bolso

2011, ISBN: 9780387094250

[ED: Gebunden], [PU: Springer-Verlag GmbH], This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial… mais…

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Evolutionary Optimization: the µGP toolkit - Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero
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Evolutionary Optimization: the µGP toolkit - encadernada, livro de bolso

ISBN: 9780387094250

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… mais…

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2011, ISBN: 9780387094250

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Ernesto Sanchez/ Massimiliano Schillaci/ Giovanni Squillero:
Evolutionary Optimization: the µGP toolkit - encadernada, livro de bolso

2011, ISBN: 0387094253

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Evolutionary Optimization: the µGP toolkit
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0387094253


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/

Dados detalhados do livro - Evolutionary Optimization: the µGP toolkit


EAN (ISBN-13): 9780387094250
ISBN (ISBN-10): 0387094253
Livro de capa dura
Livro de bolso
Ano de publicação: 2011
Editor/Editora: Springer US
178 Páginas
Peso: 0,420 kg
Língua: eng/Englisch

Livro na base de dados desde 2008-08-30T11:42:36-03:00 (Sao Paulo)
Página de detalhes modificada pela última vez em 2024-01-14T17:49:48-03:00 (Sao Paulo)
Número ISBN/EAN: 0387094253

Número ISBN - Ortografia alternativa:
0-387-09425-3, 978-0-387-09425-0
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: mejia sanchez, ernesto mejía sánchez, ernes, massimi, giovanni
Título do livro: the

Dados da editora

Autor: Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero
Título: Evolutionary Optimization: the µGP toolkit
Editora: Springer; Springer US
178 Páginas
Ano de publicação: 2011-04-07
New York; NY; US
Impresso / Feito em
Peso: 0,459 kg
Língua: Inglês
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
POD
XIII, 178 p.

BB; Artificial Intelligence; Hardcover, Softcover / 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; Computer Applications; Computer-Aided Engineering (CAD, CAE) and Design; Artificial Intelligence; Computer and Information Systems Applications; Computer-Aided Engineering (CAD, CAE) and Design; Angewandte Informatik; Computer-Aided Design (CAD); BC; EA

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

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 tool … . It is effective as a starting guide for using the tool, and is also useful for discovering advanced features and exploiting the flexibility of individual representation.” (Corrado Mencar, ACM Computing Reviews, March, 2012)

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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