EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV - International Conference Held at Leiden University, July 10-13, 2013 (Paperback, 2013 ed.)

Numerical and computational methods are nowadays used in a wide range of contexts in complex systems research, biology, physics, and engineering. Over the last decades different methodological schools have emerged with emphasis on different aspects of computation, such as nature-inspired algorithms, set oriented numerics, probabilistic systems and Monte Carlo methods. Due to the use of different terminologies and emphasis on different aspects of algorithmic performance there is a strong need for a more integrated view and opportunities for cross-fertilization across particular disciplines. These proceedings feature 20 original publications from distinguished authors in the cross-section of computational sciences, such as machine learning algorithms and probabilistic models, complex networks and fitness landscape analysis, set oriented numerics and cell mapping, evolutionary multiobjective optimization, diversity-oriented search, and the foundations of genetic programming algorithms. By presenting cutting edge results with a strong focus on foundations and integration aspects this work presents a stepping stone towards efficient, reliable, and well-analyzed methods for complex systems management and analysis.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Advances in Intelligent Systems and Computing, 227
Release date:	June 2013
First published:	2013
Editors:	Michael Emmerich • Andre Deutz • Oliver Schuetze • Thomas Back • Emilia Tantar • Alexandru-Adrian Tantar • Del Moral. P • Pierrick Legrand • Pascal Bouvry • Carlos A. Coello
Dimensions:	235 x 155 x 18mm (L x W x T)
Format:	Paperback
Pages:	324
Edition:	2013 ed.
ISBN-13:	978-3-319-01127-1
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-319-01127-8
Barcode:	9783319011271

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