Paired comparison-based Interactive Differential Evolution
We propose a system of Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are central to reducing Inte...
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| creator | Takagi, H. Pallez, D. |
| description | We propose a system of Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are central to reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the proposed IDE and tournament IGA do not need to compare whole individuals with each other but rather only to compare pairs of individuals, which largely decreases user fatigue. In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed method is superior to others from both user interface and convergence performance points of view. |
| doi_str_mv | 10.1109/NABIC.2009.5393359 |
| format | Conference Proceeding |
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In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed method is superior to others from both user interface and convergence performance points of view.</description><identifier>ISBN: 1424450535</identifier><identifier>ISBN: 9781424450534</identifier><identifier>DOI: 10.1109/NABIC.2009.5393359</identifier><identifier>LCCN: 2009907135</identifier><language>eng</language><publisher>IEEE</publisher><subject>Acceleration ; Algorithm design and analysis ; Convergence ; Differential Evolution ; Evolutionary Algorithms ; Evolutionary computation ; Fatigue ; Gaussian Mixture Model ; Genetic algorithms ; IEC standards ; Interactive Evolutionary Computation ; Noise reduction ; Paired Comparison ; Quantization ; User interfaces</subject><ispartof>2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009, p.475-480</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5393359$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,4035,4036,27904,54898</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5393359$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Takagi, H.</creatorcontrib><creatorcontrib>Pallez, D.</creatorcontrib><title>Paired comparison-based Interactive Differential Evolution</title><title>2009 World Congress on Nature & Biologically Inspired Computing (NaBIC)</title><addtitle>NABIC</addtitle><description>We propose a system of Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are central to reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the proposed IDE and tournament IGA do not need to compare whole individuals with each other but rather only to compare pairs of individuals, which largely decreases user fatigue. In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed method is superior to others from both user interface and convergence performance points of view.</description><subject>Acceleration</subject><subject>Algorithm design and analysis</subject><subject>Convergence</subject><subject>Differential Evolution</subject><subject>Evolutionary Algorithms</subject><subject>Evolutionary computation</subject><subject>Fatigue</subject><subject>Gaussian Mixture Model</subject><subject>Genetic algorithms</subject><subject>IEC standards</subject><subject>Interactive Evolutionary Computation</subject><subject>Noise reduction</subject><subject>Paired Comparison</subject><subject>Quantization</subject><subject>User interfaces</subject><isbn>1424450535</isbn><isbn>9781424450534</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT91KwzAYDchAN_cCetMXaE3yJUvi3aybFoZ6odfjS_sFIl070jrw7e1w5-bAOXB-GLsTvBCCu4e39VNVFpJzV2hwANpdsblQUinNNegZm589x40Afc2Ww_DNJygtgesb9viBMVGT1f3hiCkOfZd7HCah6kZKWI_xRNlzDIESdWPENtuc-vZnjH13y2YB24GWF16wr-3ms3zNd-8vVbne5fFcnItgjfLWW-UAjQ21lbDSoQFrAUl5g9IoUI7AT4uaBq0y0q58HQRJIAELdv-fG4lof0zxgOl3f_kKf091R4o</recordid><startdate>2009</startdate><enddate>2009</enddate><creator>Takagi, H.</creator><creator>Pallez, D.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2009</creationdate><title>Paired comparison-based Interactive Differential Evolution</title><author>Takagi, H. ; Pallez, D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i2009-1f874b8b8493a78fc82365fd3883ae4b7a274349e3b305dda847286bcf1e23e13</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Acceleration</topic><topic>Algorithm design and analysis</topic><topic>Convergence</topic><topic>Differential Evolution</topic><topic>Evolutionary Algorithms</topic><topic>Evolutionary computation</topic><topic>Fatigue</topic><topic>Gaussian Mixture Model</topic><topic>Genetic algorithms</topic><topic>IEC standards</topic><topic>Interactive Evolutionary Computation</topic><topic>Noise reduction</topic><topic>Paired Comparison</topic><topic>Quantization</topic><topic>User interfaces</topic><toplevel>online_resources</toplevel><creatorcontrib>Takagi, H.</creatorcontrib><creatorcontrib>Pallez, D.</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>Takagi, H.</au><au>Pallez, D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Paired comparison-based Interactive Differential Evolution</atitle><btitle>2009 World Congress on Nature & Biologically Inspired Computing (NaBIC)</btitle><stitle>NABIC</stitle><date>2009</date><risdate>2009</risdate><spage>475</spage><epage>480</epage><pages>475-480</pages><isbn>1424450535</isbn><isbn>9781424450534</isbn><abstract>We propose a system of Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. 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| ispartof | 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009, p.475-480 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Acceleration Algorithm design and analysis Convergence Differential Evolution Evolutionary Algorithms Evolutionary computation Fatigue Gaussian Mixture Model Genetic algorithms IEC standards Interactive Evolutionary Computation Noise reduction Paired Comparison Quantization User interfaces |
| title | Paired comparison-based Interactive Differential Evolution |
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