Overview
- Comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems
- Presents selected results of the EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation meeting held in Leiden, Netherlands in July 2013
- Offers the latest research on probability, set-oriented numerics and evolutionary computation
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 662)
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Table of contents (9 chapters)
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Evolutionary Methods in Computational Game Theory
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Algorithm Design for Real World Challenges
Editors and Affiliations
Bibliographic Information
Book Title: EVOLVE – A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII
Editors: Michael Emmerich, André Deutz, Oliver Schütze, Pierrick Legrand, Emilia Tantar, Alexandru-Adrian Tantar
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-49325-1
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-49324-4Published: 05 May 2017
Softcover ISBN: 978-3-319-84133-5Published: 20 July 2018
eBook ISBN: 978-3-319-49325-1Published: 27 April 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: VIII, 210
Number of Illustrations: 39 b/w illustrations, 36 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Probability Theory and Stochastic Processes, Mathematics of Computing, Computational Mathematics and Numerical Analysis