Estimation of Distribution Algorithm Based on Probabilistic Grammar with Latent Annotations

Evolutionary algorithms (EAs) are optimization methods and are based on the concept of natural evolution. Recently, growing interests has been observed on applying estimation of distribution techniques to EAs (EDAs). Although probabilistic context free grammar (PCFG) is a widely used model in EDAs f...

Full description

Saved in:
Bibliographic Details
Published inTransactions of the Japanese Society for Artificial Intelligence Vol. 23; no. 1; pp. 13 - 26
Main Authors Hasegawa, Yoshihiko, Iba, Hitoshi
Format Journal Article
LanguageEnglish
Published Tokyo Japan Science and Technology Agency 2008
Subjects
Algorithms
Annotations
Evolution
Expert systems
Grammars
Mathematical models
Probabilistic methods
Probability theory
Online AccessGet full text
ISSN1346-0714
1346-8030
1346-8030
DOI10.1527/tjsai.23.13

Cover

Abstract Evolutionary algorithms (EAs) are optimization methods and are based on the concept of natural evolution. Recently, growing interests has been observed on applying estimation of distribution techniques to EAs (EDAs). Although probabilistic context free grammar (PCFG) is a widely used model in EDAs for program evolution, it is not able to estimate the building blocks from promising solutions because it takes advantage of the context freedom assumption. We have proposed a new program evolution algorithm based on PCFG with latent annotations which weaken the context freedom assumption. Computational experiments on two subjects (the royal tree problem and the DMAX problem) demonstrate that our new approach is highly effective compared to prior approaches including the conventional GP.
AbstractList Evolutionary algorithms (EAs) are optimization methods and are based on the concept of natural evolution. Recently, growing interests has been observed on applying estimation of distribution techniques to EAs (EDAs). Although probabilistic context free grammar (PCFG) is a widely used model in EDAs for program evolution, it is not able to estimate the building blocks from promising solutions because it takes advantage of the context freedom assumption. We have proposed a new program evolution algorithm based on PCFG with latent annotations which weaken the context freedom assumption. Computational experiments on two subjects (the royal tree problem and the DMAX problem) demonstrate that our new approach is highly effective compared to prior approaches including the conventional GP.
Author Iba, Hitoshi
Hasegawa, Yoshihiko
Author_xml – sequence: 1
  givenname: Yoshihiko
  surname: Hasegawa
  fullname: Hasegawa, Yoshihiko
  organization: Department of Frontier Informatics, Graduate School of Frontier Sciences, The University of Tokyo
– sequence: 2
  givenname: Hitoshi
  surname: Iba
  fullname: Iba, Hitoshi
  organization: Department of Frontier Informatics, Graduate School of Frontier Sciences, The University of Tokyo
BookMark eNp9kM1OAjEUhRuDiYisfIFJXLjQwXba6QxLREQTEl3oykXTllZLZlpsOyG8vRVYkejq_uS7J-eec9CzzioALhEcobKo7uIqcDMq8AjhE9BHmNC8hhj2Dj2sEDkDwxCMgLAuYVriPviYhWhaHo2zmdPZgwnRG9Ht5knz6byJX212z4NaZmn16p3gwjQJMzKbe9623GebBGULHpWN2cRaF3d64QKcat4ENTzUAXh_nL1Nn_LFy_x5OlnkElUlzmtZSVjzZcFpaiqK9ZJryZGQSkshCBaqhktdElioEhZjQSslFdG0lJrSAuIBuN3rdnbNtxveNGzt01N-yxBkv9mwXTaswAzhhF_v8bV3350KkbUmSNU03CrXBTZGhGJE6nEir47Ileu8Tb8wRCo6JqTc6aE9Jb0LwSvNpNknED03zR8ebo5u_nP8A4dBlZw
CitedBy_id crossref_primary_10_1527_tjsai_24_80
crossref_primary_10_1527_tjsai_25_340
Cites_doi 10.1007/978-3-662-04726-2
10.1007/978-3-540-24854-5_78
10.7551/mitpress/3242.003.0041
10.1145/1068009.1068134
10.1109/CEC.2004.1330895
10.1109/CEC.2003.1299869
10.1007/978-3-540-31989-4_4
10.1109/CEC.2003.1299866
10.3115/1219840.1219850
10.1007/3-540-46033-0_21
10.1007/978-3-540-31989-4_14
10.1145/1068009.1068305
10.1527/tjsai.22.37
10.1007/978-1-4615-1539-5
ContentType Journal Article
Copyright Copyright Japan Science and Technology Agency 2008
Copyright_xml – notice: Copyright Japan Science and Technology Agency 2008
DBID AAYXX
CITATION
7SC
8FD
JQ2
L7M
L~C
L~D
ADTOC
UNPAY
DOI 10.1527/tjsai.23.13
DatabaseName CrossRef
Computer and Information Systems Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
Unpaywall for CDI: Periodical Content
Unpaywall
DatabaseTitle CrossRef
Computer and Information Systems Abstracts
Technology Research Database
Computer and Information Systems Abstracts – Academic
Advanced Technologies Database with Aerospace
ProQuest Computer Science Collection
Computer and Information Systems Abstracts Professional
DatabaseTitleList Computer and Information Systems Abstracts
Computer and Information Systems Abstracts
Database_xml – sequence: 1
  dbid: UNPAY
  name: Unpaywall
  url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/
  sourceTypes: Open Access Repository
DeliveryMethod fulltext_linktorsrc
Discipline Computer Science
EISSN 1346-8030
EndPage 26
ExternalDocumentID 10.1527/tjsai.23.13
3180063181
10_1527_tjsai_23_13
GroupedDBID 123
2WC
AAYXX
ABJNI
ACGFS
ALMA_UNASSIGNED_HOLDINGS
ARCSS
CITATION
CS3
E3Z
EBS
EJD
JSF
KQ8
OK1
PQQKQ
RJT
XSB
7SC
8FD
JQ2
L7M
L~C
L~D
ADTOC
UNPAY
ID FETCH-LOGICAL-c1753-8c7c08ad2a67c0763fdafca1bcefcbb43be80df5402e5029b67ece4f65cf66203
IEDL.DBID UNPAY
ISSN 1346-0714
1346-8030
IngestDate Tue Aug 19 23:21:06 EDT 2025
Wed Oct 01 13:34:06 EDT 2025
Mon Jun 30 06:08:01 EDT 2025
Thu Apr 24 23:03:48 EDT 2025
Tue Jul 01 03:45:32 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed false
IsScholarly true
Issue 1
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c1753-8c7c08ad2a67c0763fdafca1bcefcbb43be80df5402e5029b67ece4f65cf66203
Notes ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
content type line 23
OpenAccessLink https://proxy.k.utb.cz/login?url=https://www.jstage.jst.go.jp/article/tjsai/23/1/23_1_13/_pdf
PQID 1476944513
PQPubID 2029095
PageCount 14
ParticipantIDs unpaywall_primary_10_1527_tjsai_23_13
proquest_miscellaneous_914631489
proquest_journals_1476944513
crossref_citationtrail_10_1527_tjsai_23_13
crossref_primary_10_1527_tjsai_23_13
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2008-00-00
20080101
PublicationDateYYYYMMDD 2008-01-01
PublicationDate_xml – year: 2008
  text: 2008-00-00
PublicationDecade 2000
PublicationPlace Tokyo
PublicationPlace_xml – name: Tokyo
PublicationTitle Transactions of the Japanese Society for Artificial Intelligence
PublicationYear 2008
Publisher Japan Science and Technology Agency
Publisher_xml – name: Japan Science and Technology Agency
References 22
23
24
25
26
27
28
29
YANAI KOSUKE (30) 2005; 46
KURAHASHI SETSUYA (13) 2003; 18
10
11
12
14
15
16
17
18
19
1
2
3
4
5
6
7
8
9
20
21
References_xml – ident: 2
– ident: 18
– ident: 14
  doi: 10.1007/978-3-662-04726-2
– ident: 12
– ident: 28
  doi: 10.1007/978-3-540-24854-5_78
– ident: 10
– ident: 4
  doi: 10.7551/mitpress/3242.003.0041
– ident: 16
  doi: 10.1145/1068009.1068134
– ident: 9
– ident: 7
– ident: 24
  doi: 10.1109/CEC.2004.1330895
– ident: 22
– ident: 23
  doi: 10.1109/CEC.2003.1299869
– ident: 3
– ident: 21
  doi: 10.1007/978-3-540-31989-4_4
– ident: 5
– ident: 27
  doi: 10.1109/CEC.2003.1299866
– ident: 1
– volume: 18
  start-page: 487
  issn: 0912-8085
  issue: 5
  year: 2003
  ident: 13
  publication-title: 人工知能学会誌
– ident: 17
  doi: 10.3115/1219840.1219850
– ident: 11
– ident: 20
  doi: 10.1007/3-540-46033-0_21
– ident: 19
– volume: 46
  start-page: 111
  issn: 0387-5806
  issue: SIG10(TOM12)
  year: 2005
  ident: 30
  publication-title: 情報処理学会論文誌
– ident: 26
  doi: 10.1007/978-3-540-31989-4_14
– ident: 29
  doi: 10.1145/1068009.1068305
– ident: 6
– ident: 8
  doi: 10.1527/tjsai.22.37
– ident: 15
  doi: 10.1007/978-1-4615-1539-5
– ident: 25
SSID ssib008501343
ssib047348305
ssib000961560
ssj0057238
ssib006575950
Score 1.6811042
Snippet Evolutionary algorithms (EAs) are optimization methods and are based on the concept of natural evolution. Recently, growing interests has been observed on...
SourceID unpaywall
proquest
crossref
SourceType Open Access Repository
Aggregation Database
Enrichment Source
Index Database
StartPage 13
SubjectTerms Algorithms
Annotations
Evolution
Expert systems
Grammars
Mathematical models
Probabilistic methods
Probability theory
Title Estimation of Distribution Algorithm Based on Probabilistic Grammar with Latent Annotations
URI https://www.proquest.com/docview/1476944513
https://www.proquest.com/docview/914631489
https://www.jstage.jst.go.jp/article/tjsai/23/1/23_1_13/_pdf
UnpaywallVersion publishedVersion
Volume 23
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAFT
  databaseName: Open Access Digital Library
  customDbUrl:
  eissn: 1346-8030
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0057238
  issn: 1346-8030
  databaseCode: KQ8
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html
  providerName: Colorado Alliance of Research Libraries
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwEB612wMnylMsaisfygUpTztOIvWyQEvFoyoSKxUhZNmOvXRZktVuVgh-PePEWR5CCHFJoniUh-3xfJPMfANwzBJtcjTUqOK5Cpgss0BSdFYKlsYIYFWRdOljry_4-ZS9uMquduBkyIVxYZVzxEUz43bhrAnny8h3YtTO1_I6SmmU4EYkIqGRWFZ2F_Z4hkh8BHvTi8vJu87HYrzLzRmOC5zMPj0vQ2-_u1KY0jChvxqkHyjzxqZeyq9f5GLxk8E524cPw6P2cSafwk2rQv3tNxbH_32XW3DTI1Ey6SVvw46p78D-UOWBeKW_C-9PcRXoExxJY8kzx7Tri2SRyWLWrK7bj5_JE7SGFcFTlytcIVzErSOAJs9X0iXHEfe5l7xCXFu3ZFLXTR8AsL4H07PTt0_PA1-SIdCO0jModK7jQlap5HiAa5OtpNUyUdpYrRSjyhRxZREGpiaL01Lx3GjDLM-05TyN6X0Y1U1tHgDRtLBcUufTWEYNk1IybdCeMlOVeWbG8HgYF6E9X7krm7EQzm_BQRRdFwrXe3QMx1vhZU_T8Wexg2GAhdfVNTo_OS8dTxs2k20zapn7dSJr02zWokSDQtFzLMfwaDsv_nanh_8odwCjdrUxh4hsWnUEuy_fFEd-Gn8HLsD-WA
linkProvider Unpaywall
linkToUnpaywall http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwEB6V7YETLS-xqEU-lAtSnnacROplgZYKQdUDKxUhZNmOvXRZktVuVlX76xknzvIQQohLEsWjPGyP55tk5huAI5Zok6OhRhXPVcBkmQWSorNSsDRGAKuKpEsfe3_Oz6bs7WV2uQPHQy6MC6ucIy6aGbcLZ004X0a-E6N2vpZXUUqjBDciEQmNxLKyd2CXZ4jER7A7Pb-YfOx8LMa73JzhuMDJ7NPzMvT2uyuFKQ0T-qtB-oEy727qpby5lovFTwbndA8-D4_ax5l8DTetCvXtbyyO__su-3DPI1Ey6SXvw46pH8DeUOWBeKV_CJ9OcBXoExxJY8lrx7Tri2SRyWLWrK7aL9_IS7SGFcFTFytcIVzErSOAJm9W0iXHEfe5l7xDXFu3ZFLXTR8AsH4E09OTD6_OAl-SIdCO0jModK7jQlap5HiAa5OtpNUyUdpYrRSjyhRxZREGpiaL01Lx3GjDLM-05TyN6WMY1U1tngDRtLBcUufTWEYNk1IybdCeMlOVeWbG8GIYF6E9X7krm7EQzm_BQRRdFwrXe3QMR1vhZU_T8Wexg2GAhdfVNTo_OS8dTxs2k20zapn7dSJr02zWokSDQtFzLMfwfDsv_nanp_8odwCjdrUxh4hsWvXMT-DvPhH9Yw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Estimation+of+Distribution+Algorithm+Based+on+Probabilistic+Grammar+with+Latent+Annotations&rft.jtitle=Transactions+of+the+Japanese+Society+for+Artificial+Intelligence&rft.au=Hasegawa%2C+Yoshihiko&rft.au=Iba%2C+Hitoshi&rft.date=2008&rft.issn=1346-0714&rft.eissn=1346-8030&rft.volume=23&rft.issue=1&rft.spage=13&rft.epage=26&rft_id=info:doi/10.1527%2Ftjsai.23.13&rft.externalDBID=n%2Fa&rft.externalDocID=10_1527_tjsai_23_13
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1346-0714&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1346-0714&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1346-0714&client=summon