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Artificial evolution : 13th International Conference, Évolution Artificielle, EA 2017, Paris, France, October 25-27, 2017, Revised selected papers

Author: Evelyne Lutton; Pierrick Legrand; Pierre Parrend; Nicolas Monmarché; Marc Schoenauer
Publisher: Cham, Switzerland : Springer, 2018.
Series: Lecture notes in computer science, 10764.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Summary:
This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Conference on Artificial Evolution, EA 2017, held in Paris, France, in October 2017. The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution,  Read more...
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Genre/Form: Electronic books
Conference papers and proceedings
Congresses
Additional Physical Format: Printed edition:
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Evelyne Lutton; Pierrick Legrand; Pierre Parrend; Nicolas Monmarché; Marc Schoenauer
ISBN: 9783319781334 3319781332
OCLC Number: 1029606044
Notes: Includes author index.
Description: 1 online resource (xvi, 231 pages) : illustrations
Series Title: Lecture notes in computer science, 10764.; LNCS sublibrary., SL 1,, Theoretical computer science and general issues.
Other Titles: EA 2017
Responsibility: Evelyne Lutton, Pierrick Legrand, Pierre Parrend, Nicolas Monmarché, Marc Schoenauer (eds.).

Abstract:

This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Conference on Artificial Evolution, EA 2017, held in Paris, France, in October 2017. The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmics and modeling, implementations, application of evolutionary paradigms to the real world (industry, biosciences ...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms ...), memetic algorithms, multi-objective optimisation, constraint handling, parallel algorithms, dynamic optimization, machine learning and hybridization with other soft computing techniques.

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