000 03731nam a22004815i 4500
001 292404
003 MX-SnUAN
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007 cr nn 008mamaa
008 150903s2013 gw | o |||| 0|eng d
020 _a9783319011288
_99783319011288
024 7 _a10.1007/9783319011288
_2doi
035 _avtls000345872
039 9 _a201509030909
_bVLOAD
_c201405050326
_dVLOAD
_y201402061346
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQ342
100 1 _aEmmerich, Michael.
_eeditor.
_9324143
245 1 0 _aEVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV :
_bInternational Conference held at Leiden University, July 10-13, 2013 /
_cedited by Michael Emmerich, Andre Deutz, Oliver Schuetze, Thomas Bäck, Emilia Tantar, Alexandru-Adrian Tantar, Pierre Del Moral, Pierrick Legrand, Pascal Bouvry, Carlos A. Coello.
264 1 _aHeidelberg :
_bSpringer International Publishing :
_bImprint: Springer,
_c2013.
300 _axiv, 324 páginas 140 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aAdvances in Intelligent Systems and Computing,
_x2194-5357 ;
_v227
500 _aSpringer eBooks
505 0 _aMachine Learning and Probabilistic Models -- Complex Networks and Evolutionary Computation -- Diversity Oriented Optimization -- Set-oriented Numerics and Evolutionary Multiobjective Optimization -- Genetic Programming -- Robust Optimization.
520 _aNumerical 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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aDeutz, Andre.
_eeditor.
_9324144
700 1 _aSchuetze, Oliver.
_eeditor.
_9324145
700 1 _aBäck, Thomas.
_eeditor.
_9324146
700 1 _aTantar, Emilia.
_eeditor.
_9324147
700 1 _aTantar, Alexandru-Adrian.
_eeditor.
_9324148
700 1 _aMoral, Pierre Del.
_eeditor.
_9324149
700 1 _aLegrand, Pierrick.
_eeditor.
_9324150
700 1 _aBouvry, Pascal.
_eeditor.
_9324151
700 1 _aCoello, Carlos A.
_eeditor.
_9324152
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9783319011271
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-319-01128-8
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c292404
_d292404