Can OneMax help optimizing LeadingOnes using the EA+RL method?

There exist optimization problems with the target objective, which is to be optimized, and several extra objectives, which can be helpful in the optimization process. The EA+RL method is designed to control optimization algorithms which solve problems with extra objectives. The method is based on th...

Full description

Saved in:
Bibliographic Details
Main Authors: Buzdalov, Maxim, Buzdalova, Arina
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Evolutionary computation
Learning (artificial intelligence)
Markov processes
Optimization
Silicon
Switches
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 1768
container_issue
container_start_page 1762
container_title
container_volume
creator Buzdalov, Maxim
Buzdalova, Arina
description There exist optimization problems with the target objective, which is to be optimized, and several extra objectives, which can be helpful in the optimization process. The EA+RL method is designed to control optimization algorithms which solve problems with extra objectives. The method is based on the use of reinforcement learning for adaptive online selection of objectives.
doi_str_mv 10.1109/CEC.2015.7257100
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_7257100</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7257100</ieee_id><sourcerecordid>7257100</sourcerecordid><originalsourceid>FETCH-LOGICAL-i123t-b31149cf9aa9dcef8592982cf57a930f658fcd827e41aab1b44109262bf18acf3</originalsourceid><addsrcrecordid>eNotj99LwzAUhaMouE3fBV_yLq25adLkviij1B9QGYiCb-O2TWxk7cpaYfrXW3FP3-EcOPAxdgkiBhB4k-VZLAXo2EhtQIgjNgdlEI1CaY7ZDFBBJIRMT6YsLEbG2PczNh-GTyFAacAZu82o46vOPdOeN27T820_hjb8hO6DF47qidM68K_hrxkbx_Pl9UvBWzc22_runJ162gzu4sAFe7vPX7PHqFg9PGXLIgogkzEqEwCFlUcirCvnrUaJVlZeG8JE-FRbX9VWGqeAqIRSqUlQprL0YKnyyYJd_f8G59y634WWdt_rg3fyC58tSNk</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Can OneMax help optimizing LeadingOnes using the EA+RL method?</title><source>IEEE Xplore All Conference Series</source><creator>Buzdalov, Maxim ; Buzdalova, Arina</creator><creatorcontrib>Buzdalov, Maxim ; Buzdalova, Arina</creatorcontrib><description>There exist optimization problems with the target objective, which is to be optimized, and several extra objectives, which can be helpful in the optimization process. The EA+RL method is designed to control optimization algorithms which solve problems with extra objectives. The method is based on the use of reinforcement learning for adaptive online selection of objectives.</description><identifier>ISSN: 1089-778X</identifier><identifier>EISSN: 1941-0026</identifier><identifier>EISBN: 1479974927</identifier><identifier>EISBN: 9781479974924</identifier><identifier>DOI: 10.1109/CEC.2015.7257100</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Evolutionary computation ; Learning (artificial intelligence) ; Markov processes ; Optimization ; Silicon ; Switches</subject><ispartof>2015 IEEE Congress on Evolutionary Computation (CEC), 2015, p.1762-1768</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7257100$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,23930,23931,25140,27925,54555,54796,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7257100$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Buzdalov, Maxim</creatorcontrib><creatorcontrib>Buzdalova, Arina</creatorcontrib><title>Can OneMax help optimizing LeadingOnes using the EA+RL method?</title><title>2015 IEEE Congress on Evolutionary Computation (CEC)</title><addtitle>CEC</addtitle><description>There exist optimization problems with the target objective, which is to be optimized, and several extra objectives, which can be helpful in the optimization process. The EA+RL method is designed to control optimization algorithms which solve problems with extra objectives. The method is based on the use of reinforcement learning for adaptive online selection of objectives.</description><subject>Algorithm design and analysis</subject><subject>Evolutionary computation</subject><subject>Learning (artificial intelligence)</subject><subject>Markov processes</subject><subject>Optimization</subject><subject>Silicon</subject><subject>Switches</subject><issn>1089-778X</issn><issn>1941-0026</issn><isbn>1479974927</isbn><isbn>9781479974924</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2015</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj99LwzAUhaMouE3fBV_yLq25adLkviij1B9QGYiCb-O2TWxk7cpaYfrXW3FP3-EcOPAxdgkiBhB4k-VZLAXo2EhtQIgjNgdlEI1CaY7ZDFBBJIRMT6YsLEbG2PczNh-GTyFAacAZu82o46vOPdOeN27T820_hjb8hO6DF47qidM68K_hrxkbx_Pl9UvBWzc22_runJ162gzu4sAFe7vPX7PHqFg9PGXLIgogkzEqEwCFlUcirCvnrUaJVlZeG8JE-FRbX9VWGqeAqIRSqUlQprL0YKnyyYJd_f8G59y634WWdt_rg3fyC58tSNk</recordid><startdate>20150501</startdate><enddate>20150501</enddate><creator>Buzdalov, Maxim</creator><creator>Buzdalova, Arina</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20150501</creationdate><title>Can OneMax help optimizing LeadingOnes using the EA+RL method?</title><author>Buzdalov, Maxim ; Buzdalova, Arina</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i123t-b31149cf9aa9dcef8592982cf57a930f658fcd827e41aab1b44109262bf18acf3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithm design and analysis</topic><topic>Evolutionary computation</topic><topic>Learning (artificial intelligence)</topic><topic>Markov processes</topic><topic>Optimization</topic><topic>Silicon</topic><topic>Switches</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Buzdalov, Maxim</creatorcontrib><creatorcontrib>Buzdalova, Arina</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Buzdalov, Maxim</au><au>Buzdalova, Arina</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Can OneMax help optimizing LeadingOnes using the EA+RL method?</atitle><btitle>2015 IEEE Congress on Evolutionary Computation (CEC)</btitle><stitle>CEC</stitle><date>2015-05-01</date><risdate>2015</risdate><spage>1762</spage><epage>1768</epage><pages>1762-1768</pages><issn>1089-778X</issn><eissn>1941-0026</eissn><eisbn>1479974927</eisbn><eisbn>9781479974924</eisbn><abstract>There exist optimization problems with the target objective, which is to be optimized, and several extra objectives, which can be helpful in the optimization process. The EA+RL method is designed to control optimization algorithms which solve problems with extra objectives. The method is based on the use of reinforcement learning for adaptive online selection of objectives.</abstract><pub>IEEE</pub><doi>10.1109/CEC.2015.7257100</doi><tpages>7</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1089-778X
ispartof 2015 IEEE Congress on Evolutionary Computation (CEC), 2015, p.1762-1768
issn 1089-778X
1941-0026
language eng
recordid cdi_ieee_primary_7257100
source IEEE Xplore All Conference Series
subjects Algorithm design and analysis
Evolutionary computation
Learning (artificial intelligence)
Markov processes
Optimization
Silicon
Switches
title Can OneMax help optimizing LeadingOnes using the EA+RL method?
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T01%3A49%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Can%20OneMax%20help%20optimizing%20LeadingOnes%20using%20the%20EA+RL%20method?&rft.btitle=2015%20IEEE%20Congress%20on%20Evolutionary%20Computation%20(CEC)&rft.au=Buzdalov,%20Maxim&rft.date=2015-05-01&rft.spage=1762&rft.epage=1768&rft.pages=1762-1768&rft.issn=1089-778X&rft.eissn=1941-0026&rft_id=info:doi/10.1109/CEC.2015.7257100&rft.eisbn=1479974927&rft.eisbn_list=9781479974924&rft_dat=%3Cieee_CHZPO%3E7257100%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i123t-b31149cf9aa9dcef8592982cf57a930f658fcd827e41aab1b44109262bf18acf3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=7257100&rfr_iscdi=true