Verfügbarkeit: Machine learning for evolution strategies

Machine learning for evolution strategies:

Gespeichert in:

Bibliographische Detailangaben
1. Verfasser:	Kramer, Oliver (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	[Cham] Springer [2016]
Schriftenreihe:	Studies in Big Data volume 20 (2016)
Schlagworte:	Engineering Data mining Artificial intelligence Computer simulation Sociophysics Econophysics Computational intelligence Computational Intelligence Simulation and Modeling Data Mining and Knowledge Discovery Socio- and Econophysics, Population and Evolutionary Models Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen
Online-Zugang:	BTU01 FAB01 FAW01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract
Beschreibung:	1 Online-Ressource (IX, 124 Seiten)
ISBN:	9783319333830
DOI:	10.1007/978-3-319-33383-0

Internformat

MARC


LEADER	00000nmm a2200000zcb4500
001	BV043579626
003	DE-604
005	20160908
007	cr\|uuu---uuuuu
008	160601s2016 \|\|\|\| o\|\|u\| \|\|\|\|\|\|eng d
020			\|a 9783319333830 \|c Online \|9 978-3-319-33383-0
024	7		\|a 10.1007/978-3-319-33383-0 \|2 doi
035			\|a (ZDB-2-ENG)978-3-319-33383-0
035			\|a (OCoLC)951072361
035			\|a (DE-599)BVBBV043579626
040			\|a DE-604 \|b ger \|e rda
041	0		\|a eng
049			\|a DE-706 \|a DE-1046 \|a DE-1043 \|a DE-Aug4 \|a DE-898 \|a DE-861 \|a DE-573 \|a DE-859 \|a DE-863 \|a DE-634 \|a DE-862 \|a DE-92
082	0		\|a 006.3 \|2 23
084			\|a ST 300 \|0 (DE-625)143650: \|2 rvk
100	1		\|a Kramer, Oliver \|e Verfasser \|0 (DE-588)1107031117 \|4 aut
245	1	0	\|a Machine learning for evolution strategies \|c Oliver Kramer
264		1	\|a [Cham] \|b Springer \|c [2016]
264		4	\|c © 2016
300			\|a 1 Online-Ressource (IX, 124 Seiten)
336			\|b txt \|2 rdacontent
337			\|b c \|2 rdamedia
338			\|b cr \|2 rdacarrier
490	1		\|a Studies in Big Data \|v volume 20 (2016)
650		4	\|a Engineering
650		4	\|a Data mining
650		4	\|a Artificial intelligence
650		4	\|a Computer simulation
650		4	\|a Sociophysics
650		4	\|a Econophysics
650		4	\|a Computational intelligence
650		4	\|a Computational Intelligence
650		4	\|a Simulation and Modeling
650		4	\|a Data Mining and Knowledge Discovery
650		4	\|a Socio- and Econophysics, Population and Evolutionary Models
650		4	\|a Artificial Intelligence (incl. Robotics)
650		4	\|a Ingenieurwissenschaften
650		4	\|a Künstliche Intelligenz
650	0	7	\|a Maschinelles Lernen \|0 (DE-588)4193754-5 \|2 gnd \|9 rswk-swf
689	0	0	\|a Maschinelles Lernen \|0 (DE-588)4193754-5 \|D s
689	0		\|8 1\p \|5 DE-604
776	0	8	\|i Erscheint auch als \|n Druckausgabe \|z 978-3-319-33381-6
830		0	\|a Studies in Big Data \|v volume 20 (2016) \|w (DE-604)BV041583423 \|9 20
856	4	0	\|u https://doi.org/10.1007/978-3-319-33383-0 \|x Verlag \|z URL des Erstveröffentlichers \|3 Volltext
856	4	2	\|m Springer Fremddatenuebernahme \|q application/pdf \|u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028994299&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA \|3 Inhaltsverzeichnis
856	4	2	\|m Springer Fremddatenuebernahme \|q application/pdf \|u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028994299&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA \|3 Abstract
912			\|a ZDB-2-ENG
940	1		\|q ZDB-2-ENG_2016
999			\|a oai:aleph.bib-bvb.de:BVB01-028994299
883	1		\|8 1\p \|a cgwrk \|d 20201028 \|q DE-101 \|u https://d-nb.info/provenance/plan#cgwrk
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l BTU01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FAB01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FAW01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FHA01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FHI01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FHN01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FHR01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FKE01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FRO01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FWS01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l FWS02 \|p ZDB-2-ENG \|x Verlag \|3 Volltext
966	e		\|u https://doi.org/10.1007/978-3-319-33383-0 \|l UBY01 \|p ZDB-2-ENG \|x Verlag \|3 Volltext

Datensatz im Suchindex

DE-BY-FWS_katkey	618868
_version_	1806179773384228864
adam_text	MACHINE LEARNING FOR EVOLUTION STRATEGIES / KRAMER, OLIVER : 2016 TABLE OF CONTENTS / INHALTSVERZEICHNIS PART I EVOLUTION STRATEGIES PART II MACHINE LEARNING PART III SUPERVISED LEARNING DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. MACHINE LEARNING FOR EVOLUTION STRATEGIES / KRAMER, OLIVER : 2016 ABSTRACT / INHALTSTEXT THIS 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 DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
any_adam_object	1
author	Kramer, Oliver
author_GND	(DE-588)1107031117
author_facet	Kramer, Oliver
author_role	aut
author_sort	Kramer, Oliver
author_variant	o k ok
building	Verbundindex
bvnumber	BV043579626
classification_rvk	ST 300
collection	ZDB-2-ENG
ctrlnum	(ZDB-2-ENG)978-3-319-33383-0 (OCoLC)951072361 (DE-599)BVBBV043579626
dewey-full	006.3
dewey-hundreds	000 - Computer science, information, general works
dewey-ones	006 - Special computer methods
dewey-raw	006.3
dewey-search	006.3
dewey-sort	16.3
dewey-tens	000 - Computer science, information, general works
discipline	Informatik
doi_str_mv	10.1007/978-3-319-33383-0
format	Electronic eBook
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03856nmm a2200769zcb4500</leader><controlfield tag="001">BV043579626</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20160908 </controlfield><controlfield tag="007">cr\|uuu---uuuuu</controlfield><controlfield tag="008">160601s2016 \|\|\|\| o\|\|u\| \|\|\|\|\|\|eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783319333830</subfield><subfield code="c">Online</subfield><subfield code="9">978-3-319-33383-0</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-3-319-33383-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-ENG)978-3-319-33383-0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)951072361</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV043579626</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-706</subfield><subfield code="a">DE-1046</subfield><subfield code="a">DE-1043</subfield><subfield code="a">DE-Aug4</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-861</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-859</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-634</subfield><subfield code="a">DE-862</subfield><subfield code="a">DE-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143650:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kramer, Oliver</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1107031117</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Machine learning for evolution strategies</subfield><subfield code="c">Oliver Kramer</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Cham]</subfield><subfield code="b">Springer</subfield><subfield code="c">[2016]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (IX, 124 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Studies in Big Data</subfield><subfield code="v">volume 20 (2016)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Engineering</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data mining</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Sociophysics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Econophysics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computational intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computational Intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Simulation and Modeling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data Mining and Knowledge Discovery</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Socio- and Econophysics, Population and Evolutionary Models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial Intelligence (incl. Robotics)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ingenieurwissenschaften</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Künstliche Intelligenz</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druckausgabe</subfield><subfield code="z">978-3-319-33381-6</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Studies in Big Data</subfield><subfield code="v">volume 20 (2016)</subfield><subfield code="w">(DE-604)BV041583423</subfield><subfield code="9">20</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Springer Fremddatenuebernahme</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028994299&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Springer Fremddatenuebernahme</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028994299&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Abstract</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-ENG</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-ENG_2016</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-028994299</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">BTU01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FAB01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FAW01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FHA01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FHI01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FHR01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FKE01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FRO01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FWS01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">FWS02</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-3-319-33383-0</subfield><subfield code="l">UBY01</subfield><subfield code="p">ZDB-2-ENG</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection>
id	DE-604.BV043579626
illustrated	Not Illustrated
indexdate	2024-08-01T12:14:20Z
institution	BVB
isbn	9783319333830
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-028994299
oclc_num	951072361
open_access_boolean
owner	DE-706 DE-1046 DE-1043 DE-Aug4 DE-898 DE-BY-UBR DE-861 DE-573 DE-859 DE-863 DE-BY-FWS DE-634 DE-862 DE-BY-FWS DE-92
owner_facet	DE-706 DE-1046 DE-1043 DE-Aug4 DE-898 DE-BY-UBR DE-861 DE-573 DE-859 DE-863 DE-BY-FWS DE-634 DE-862 DE-BY-FWS DE-92
physical	1 Online-Ressource (IX, 124 Seiten)
psigel	ZDB-2-ENG ZDB-2-ENG_2016
publishDate	2016
publishDateSearch	2016
publishDateSort	2016
publisher	Springer
record_format	marc
series	Studies in Big Data
series2	Studies in Big Data
spellingShingle	Kramer, Oliver Machine learning for evolution strategies Studies in Big Data Engineering Data mining Artificial intelligence Computer simulation Sociophysics Econophysics Computational intelligence Computational Intelligence Simulation and Modeling Data Mining and Knowledge Discovery Socio- and Econophysics, Population and Evolutionary Models Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen (DE-588)4193754-5 gnd
subject_GND	(DE-588)4193754-5
title	Machine learning for evolution strategies
title_auth	Machine learning for evolution strategies
title_exact_search	Machine learning for evolution strategies
title_full	Machine learning for evolution strategies Oliver Kramer
title_fullStr	Machine learning for evolution strategies Oliver Kramer
title_full_unstemmed	Machine learning for evolution strategies Oliver Kramer
title_short	Machine learning for evolution strategies
title_sort	machine learning for evolution strategies
topic	Engineering Data mining Artificial intelligence Computer simulation Sociophysics Econophysics Computational intelligence Computational Intelligence Simulation and Modeling Data Mining and Knowledge Discovery Socio- and Econophysics, Population and Evolutionary Models Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen (DE-588)4193754-5 gnd
topic_facet	Engineering Data mining Artificial intelligence Computer simulation Sociophysics Econophysics Computational intelligence Computational Intelligence Simulation and Modeling Data Mining and Knowledge Discovery Socio- and Econophysics, Population and Evolutionary Models Artificial Intelligence (incl. Robotics) Ingenieurwissenschaften Künstliche Intelligenz Maschinelles Lernen
url	https://doi.org/10.1007/978-3-319-33383-0 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028994299&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028994299&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
volume_link	(DE-604)BV041583423
work_keys_str_mv	AT krameroliver machinelearningforevolutionstrategies

Verfügbarkeit

Volltext öffnen

MARC

Datensatz im Suchindex

Ähnliche Einträge