Co-evolution of operator settings in genetic algorithms:
Gespeichert in:
Beteiligte Personen: | , |
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Format: | Buch |
Sprache: | Englisch |
Veröffentlicht: |
Edinburgh
1996
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Schriftenreihe: | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper
789 |
Schlagwörter: | |
Abstract: | Abstract: "Typical genetic algorithm implementations use operator settings that are fixed throughout a given run. Varying these settings is known to improve performance -- the problem is knowing how to vary them. One approach is to encode the operator settings into each member of the GA population, and allow them to evolve. This paper describes an empirical investigation into the effect of co-evolving operator settings, for some common problems in the genetic algorithms field. The results obtained indicate that the problem representation, and the choice of operators on the encoded operator settings are important for useful adaptation." |
Umfang: | 8 S. |
Internformat
MARC
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041 | 0 | |a eng | |
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100 | 1 | |a Tuson, Andrew |e Verfasser |4 aut | |
245 | 1 | 0 | |a Co-evolution of operator settings in genetic algorithms |c Tuson, A. ; Ross, P. |
264 | 1 | |a Edinburgh |c 1996 | |
300 | |a 8 S. | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
490 | 1 | |a University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |v 789 | |
520 | 3 | |a Abstract: "Typical genetic algorithm implementations use operator settings that are fixed throughout a given run. Varying these settings is known to improve performance -- the problem is knowing how to vary them. One approach is to encode the operator settings into each member of the GA population, and allow them to evolve. This paper describes an empirical investigation into the effect of co-evolving operator settings, for some common problems in the genetic algorithms field. The results obtained indicate that the problem representation, and the choice of operators on the encoded operator settings are important for useful adaptation." | |
650 | 7 | |a Applied statistics, operational research |2 sigle | |
650 | 7 | |a Bionics and artificial intelligence |2 sigle | |
650 | 4 | |a Evolutionary computation | |
650 | 4 | |a Genetic algorithms | |
650 | 4 | |a Operator theory | |
700 | 1 | |a Ross, Peter |e Verfasser |4 aut | |
810 | 2 | |a Department of Artificial Intelligence: DAI research paper |t University <Edinburgh> |v 789 |w (DE-604)BV010450646 |9 789 | |
943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-007399976 |
Datensatz im Suchindex
DE-BY-TUM_call_number | 0111 2001 B 6034-789 |
---|---|
DE-BY-TUM_katkey | 774522 |
DE-BY-TUM_location | 01 |
DE-BY-TUM_media_number | 040020454406 |
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any_adam_object | |
author | Tuson, Andrew Ross, Peter |
author_facet | Tuson, Andrew Ross, Peter |
author_role | aut aut |
author_sort | Tuson, Andrew |
author_variant | a t at p r pr |
building | Verbundindex |
bvnumber | BV011049520 |
ctrlnum | (OCoLC)35590600 (DE-599)BVBBV011049520 |
format | Book |
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id | DE-604.BV011049520 |
illustrated | Not Illustrated |
indexdate | 2024-12-20T10:05:26Z |
institution | BVB |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-007399976 |
oclc_num | 35590600 |
open_access_boolean | |
owner | DE-91G DE-BY-TUM |
owner_facet | DE-91G DE-BY-TUM |
physical | 8 S. |
publishDate | 1996 |
publishDateSearch | 1996 |
publishDateSort | 1996 |
record_format | marc |
series2 | University <Edinburgh> / Department of Artificial Intelligence: DAI research paper |
spellingShingle | Tuson, Andrew Ross, Peter Co-evolution of operator settings in genetic algorithms Applied statistics, operational research sigle Bionics and artificial intelligence sigle Evolutionary computation Genetic algorithms Operator theory |
title | Co-evolution of operator settings in genetic algorithms |
title_auth | Co-evolution of operator settings in genetic algorithms |
title_exact_search | Co-evolution of operator settings in genetic algorithms |
title_full | Co-evolution of operator settings in genetic algorithms Tuson, A. ; Ross, P. |
title_fullStr | Co-evolution of operator settings in genetic algorithms Tuson, A. ; Ross, P. |
title_full_unstemmed | Co-evolution of operator settings in genetic algorithms Tuson, A. ; Ross, P. |
title_short | Co-evolution of operator settings in genetic algorithms |
title_sort | co evolution of operator settings in genetic algorithms |
topic | Applied statistics, operational research sigle Bionics and artificial intelligence sigle Evolutionary computation Genetic algorithms Operator theory |
topic_facet | Applied statistics, operational research Bionics and artificial intelligence Evolutionary computation Genetic algorithms Operator theory |
volume_link | (DE-604)BV010450646 |
work_keys_str_mv | AT tusonandrew coevolutionofoperatorsettingsingeneticalgorithms AT rosspeter coevolutionofoperatorsettingsingeneticalgorithms |
Paper/Kapitel scannen lassen
Teilbibliothek Mathematik & Informatik, Berichte
Signatur: |
0111 2001 B 6034-789 Lageplan |
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Exemplar 1 | Ausleihbar Am Standort |