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020 _a9783319333830
_9978-3-319-33383-0
024 7 _a10.1007/978-3-319-33383-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aKramer, Oliver.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_956833
245 1 0 _aMachine Learning for Evolution Strategies
_h[electronic resource] /
_cby Oliver Kramer.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aIX, 124 p. 38 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6511 ;
_v20
505 0 _aPart I Evolution Strategies -- Part II Machine Learning -- Part III Supervised Learning.
520 _aThis book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.
650 0 _aComputational intelligence.
_97716
650 0 _aComputer simulation.
_95106
650 0 _aData mining.
_93907
650 0 _aSystem theory.
_93409
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aComputer Modelling.
_956834
650 2 4 _aData Mining and Knowledge Discovery.
_956835
650 2 4 _aComplex Systems.
_918136
650 2 4 _aArtificial Intelligence.
_93407
710 2 _aSpringerLink (Online service)
_956836
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319333816
776 0 8 _iPrinted edition:
_z9783319333823
776 0 8 _iPrinted edition:
_z9783319815008
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v20
_956837
856 4 0 _uhttps://doi.org/10.1007/978-3-319-33383-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79823
_d79823