Applications of Evolutionary Computing
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Evolutionary computation (EC) techniques are e?cient, nature-inspired pl- ning and optimization methods based on the principles of natural evolution and genetics. Due to their e?ciency and simple underlying principles, these me- ods can be used in the context of problem solving, optimization, and machine learning. A large and continuously increasing number of researchers and prof- sionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the…mehr

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Produktbeschreibung
Evolutionary computation (EC) techniques are e?cient, nature-inspired pl- ning and optimization methods based on the principles of natural evolution and genetics. Due to their e?ciency and simple underlying principles, these me- ods can be used in the context of problem solving, optimization, and machine learning. A large and continuously increasing number of researchers and prof- sionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and - spire researchers and professionals to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoWorkshops 2008, which consisted of a range of workshops on application-oriented aspects of EC. Since 1998, EvoWorkshops has provided a unique opportunityfor EC researchers to meet and discuss applicationaspectsofECandhasservedasanimportantlink between EC research and its application in a variety of domains. During these ten years new workshops have arisen, some have disappeared, while others have matured to become conferences of their own, such as EuroGP in 2000, EvoCOP in 2004, and EvoBIO last year.
Autorenporträt
Michael O'Neill [BSc. (UCD), PhD (UL)] is a lecturer in the Department of Computer Science and Information Systems at the University of Limerick. He has over 70 publications on biologically inspired algorithms (BIAs). He coauthored the Springer title "Grammatical Evolution -- Evolutionary Automatic Programming in an Arbitrary Language", Genetic Programming Series, 2003, 160 pp., ISBN 1-4020-7444-1. He is one of the two original developers of the Grammatical Evolution algorithm, research that spawned an annual invited tutorial at the largest evolutionary computation conference and an international workshop, and is also on a number of relevant organising committees (e.g., GECCO 2005). Michael is a regular reviewer for the leading evolutionary computation (EC) journals, namely IEEE Trans. on Evolutionary Computation, MIT Press's Evolutionary Computation, and Springer's Genetic Programming and Evolvable Hardware journal.Anthony Brabazon [B. Comm (UCD), DPA (UCD), Dip Stats (Dub), MS (Statistics) (Stanford), MS (Operations Research) (Stanford), MBA (Heriot-Watt), DBA (Kingston), FCA, ACMA] lectures at University College Dublin. His research interests include mathematical decision models, evolutionary computation, and the application of computational intelligence to the domain of finance. He has published in excess of 100 papers in journals, conferences and professional publications, and has been a member of the programme committee at both EuroGP and GECCO conferences, as well as acting as reviewer for several journals. He has also acted as consultant to a wide range of public and private companies in several countries. He currently serves as a member of the CCAB (Ireland) Consultative Committee on Accounting Standards, and is a former Secretary and Treasurer of the Irish Accounting and Finance Association. Prior to joining UCD, he worked in the banking sector, and for KPMG.