9783642003134-3642003133-Foundations in Grammatical Evolution for Dynamic Environments (Studies in Computational Intelligence, 194)

Foundations in Grammatical Evolution for Dynamic Environments (Studies in Computational Intelligence, 194)

ISBN-13: 9783642003134
ISBN-10: 3642003133
Edition: 2009
Author: Michael ONeill, Ian Dempsey, Anthony Brabazon
Publication date: 2009
Publisher: Springer
Format: Hardcover 203 pages
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Book details

ISBN-13: 9783642003134
ISBN-10: 3642003133
Edition: 2009
Author: Michael ONeill, Ian Dempsey, Anthony Brabazon
Publication date: 2009
Publisher: Springer
Format: Hardcover 203 pages

Summary

Foundations in Grammatical Evolution for Dynamic Environments (Studies in Computational Intelligence, 194) (ISBN-13: 9783642003134 and ISBN-10: 3642003133), written by authors Michael ONeill, Ian Dempsey, Anthony Brabazon, was published by Springer in 2009. With an overall rating of 4.3 stars, it's a notable title among other Economics (Microsoft Programming, Programming, Engineering, Evolution, Applied, Mathematics) books. You can easily purchase or rent Foundations in Grammatical Evolution for Dynamic Environments (Studies in Computational Intelligence, 194) (Hardcover) from BooksRun, along with many other new and used Economics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Dynamic environments abound, encompassing many real-world problems in fields as diverse as finance, engineering, biology and business. A vibrant research literature has emerged which takes inspiration from evolutionary processes to develop problem-solvers for these environments.

'Foundations in Grammatical Evolution for Dynamic Environments' is a cutting edge volume illustrating current state of the art in applying grammar-based evolutionary computation to solve real-world problems in dynamic environments. The book provides a clear introduction to dynamic environments and the types of change that can occur. This is followed by a detailed description of evolutionary computation, concentrating on the powerful Grammatical Evolution methodology. It continues by addressing fundamental issues facing all Evolutionary Algorithms in dynamic problems, such as how to adapt and generate constants, how to enhance evolvability and maintain diversity. Finally, the developed methods are illustrated with application to the real-world dynamic problem of trading on financial time-series.

The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, who are seeking to apply grammar-based evolutionary algorithms to solve problems in dynamic environments. 'Foundations in Grammatical Evolution for Dynamic Environments' is the second book dedicated to the topic of Grammatical Evolution.

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