Evolutionary Optimization: the uGP toolkit - nuovo libro

Libro nella banca dati dal 2009-06-10T03:42:25+02:00 (Zurich)
Pagina di dettaglio ultima modifica in 2023-06-14T12:44:41+02:00 (Zurich)
ISBN/EAN: 0387094261

ISBN - Stili di scrittura alternativi:
0-387-09426-1, 978-0-387-09426-7
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : sanchez, massimi, pierre tan

Dati dell'editore

Autore: Ernesto Sanchez; Massimiliano Schillaci; Giovanni Squillero
Titolo: Evolutionary Optimization: the µGP toolkit
Editore: Springer; Springer US
178 Pagine
Anno di pubblicazione: 2011-04-01
New York; NY; US
Stampato / Fatto in
Lingua: Inglese
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

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