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020 _a9783319342238
024 7 _a10.1007/978-3-319-34223-8
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA76.623
_b2016 EB
245 0 0 _aGenetic Programming Theory and Practice XIII
_cedited by Rick Riolo, W.P. Worzel, Mark Kotanchek, Arthur Kordon
264 1 _aCham
_bSpringer International Publishing
_c2016
300 _a1 recurso en línea (XX, 262 páginas)
_b69 ilustraciones, 31 ilustraciones en color
336 _aTexto (visual)
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 0 _aGenetic and Evolutionary Computation
_x1932-0167
505 0 _aEvolving Simple Symbolic Regression Models by Multi-objective Genetic Programming -- Learning Heuristics for Mining RNA Sequence-Structure Motifs -- Kaizen Programming for Feature Construction for Classification -- GP as if You Meant It: An Exercise for Mindful Practice -- nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star -- Highly Accurate Symbolic Regression with Noisy Training Data -- Using Genetic Programming for Data Science: Lessons Learned -- The Evolution of Everything (EvE) and Genetic Programming -- Lexicase selection for program synthesis: a Diversity Analysis -- Using Graph Databases to Explore the Dynamics of Genetic Programming Runs -- Predicting Product Choice with Symbolic Regression and Classification -- Multiclass Classification Through Multidimensional Clustering -- Prime-Time: Symbolic Regression takes its place in the Real World.
520 _aThese contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
988 _aEBOOK, EBSPRINGER, GOBI_sep2018
650 7 _aProgramación genética (Informática)
_9469951
_2embne
_xCongresos y asambleas
700 1 _aKordon, Arthur.
_eeditor literario
_9101546
_0Local
_1http://viaf.org/viaf/103701121
700 1 _aKotanchek, Mark
_eeditor literario
_0Local
_0http://id.loc.gov/authorities/names/n2015186544
_1http://viaf.org/viaf/316791016
_9101545
700 1 _aRiolo, Rick.
_eeditor literario
_9101543
_0Local
_0http://id.loc.gov/authorities/names/n88650378
_1http://viaf.org/viaf/44600261
700 1 _aWorzel, W.P.
_eeditor literario
_9101544
_0Local
_0http://id.loc.gov/authorities/names/n2003015158
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-34223-8zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9783319342238
907 _a.b12981102
_b10-10-17
_c08-03-17
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