This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2009 Fifth International Conference on Natural Computation
Interactive Population-Based Incremental Learning for Problems with Implicit Performance Indices
Tianjian, China
August 14-August 16
ISBN: 978-0-7695-3736-8
ASCII Text
x 
 
Haifeng You, Xufa Wang, "Interactive Population-Based Incremental Learning for Problems with Implicit Performance Indices," 2013 International Conference on Computing, Networking and Communications (ICNC), vol. 4, pp. 311-315, 2009 Fifth International Conference on Natural Computation, 2009.
 
 
BibTex
x
 
@article{ 10.1109/ICNC.2009.211,
author = {Haifeng You and Xufa Wang},
title = {Interactive Population-Based Incremental Learning for Problems with Implicit Performance Indices},
journal ={2013 International Conference on Computing, Networking and Communications (ICNC)},
volume = {4},
year = {2009},
isbn = {978-0-7695-3736-8},
pages = {311-315},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICNC.2009.211},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - 2013 International Conference on Computing, Networking and Communications (ICNC)
TI - Interactive Population-Based Incremental Learning for Problems with Implicit Performance Indices
SN - 978-0-7695-3736-8
SP311
EP315
A1 - Haifeng You,
A1 - Xufa Wang,
PY - 2009
KW - interactive population-based incremental learning
KW - interactive evolutionary computation
KW - implicit performance indices optimization
KW - fashion design
KW - user fatigue
VL - 4
JA - 2013 International Conference on Computing, Networking and Communications (ICNC)
ER -
 
An interactive population-based incremental learning (IPBIL) algorithm has been proposed to optimize problems with implicit performance indices, which were traditionally solved by using interactive evolutionary computation (IEC). That is expected to reduce user fatigue, which is a key limitation of IEC, because users only need to select some good individuals rather than evaluate all individuals when using IPBIL. To compare the performance of IEC and IPBIL, they were applied to a fashion design system, a problem with implicit performance indices. Experimental results indicate that although IPBIL needs more generations to find a satisfactory design, it needs less time consumption and much fewer mouse clicks than IEC. Accordingly, compared with IEC, IPBIL can significantly reduce user fatigue.
Index Terms:
interactive population-based incremental learning, interactive evolutionary computation, implicit performance indices optimization, fashion design, user fatigue
Citation:
Haifeng You, Xufa Wang, "Interactive Population-Based Incremental Learning for Problems with Implicit Performance Indices," icnc, vol. 4, pp.311-315, 2009 Fifth International Conference on Natural Computation, 2009
Usage of this product signifies your acceptance of the Terms of Use.