User's Attention Knowledge Learning in Interactive Evolutionary Computation

被引：0
|
作者：
Hao Guo-Sheng [1 ,2 ]
Gong Dun-Wei [1 ]
Yuan Jie [1 ]
Yan Yu-Ruo [2 ]
Yan Jun-Rong [2 ]
机构：
[1] China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221008, Jiangsu, Peoples R China
[2] Xuzhou Normal Univ, Sch Comp Sci & Technol, Xuzhou 221116, Jiangsu, Peoples R China
来源：
CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年
关键词：
Evolutionary Computation; Interaction; User's Attention; Knowledge Learning; OPTIMIZATION; ALGORITHM;
D O I：
10.1109/CCDC.2009.5192415
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A user's attention in interactive evolutionary computation(IEC) is an important issue. The methods to learn the user's attention knowledge in IEC are studied in this paper. Firstly, the definition of the user's attention is given. Secondly, the user's attention on gene sense unit and some related theorems are given. Based on these theorems, the methods to learn the user's attention knowledge are presented. Thirdly, a new method to improve the performance of IEC based on the user's attention knowledge is given. The experiments validate the efficiency of the methods. The study on the user's attention in IEC establishes a necessary foundation for reducing users' fatigue in IEC.
引用
收藏
页码：4270 / +
页数：3
相关论文
共 50 条
  • [1] User Fatigue in Interactive Evolutionary Computation
    Yan Jun-Rong
    Min Yong
    MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, PTS 1 AND 2, 2011, 48-49 : 1333 - 1336
  • [2] Knowledge Learning in Interactive Evolutionary Computation Based on Information Flow
    Kong Li-Fang
    Zhang Hong
    Shi Hong
    WISM: 2009 INTERNATIONAL CONFERENCE ON WEB INFORMATION SYSTEMS AND MINING, PROCEEDINGS, 2009, : 39 - +
  • [3] Interactive evolutionary computation in modelling user preferences
    Kuzma, Miron
    Andrejková, Gabriela
    Advances in Intelligent Systems and Computing, 2015, 316 : 341 - 350
  • [4] Knowledge Learning for Evolutionary Computation
    Jiang, Yi
    Zhan, Zhi-Hui
    Chen Tan, Kay
    Zhang, Jun
    IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2025, 29 (01) : 16 - 30
  • [5] Estimation of Influence of Each Variable on User's Evaluation in Interactive Evolutionary Computation
    Funaki, Ryohei
    Sugimoto, Kentaro
    Murata, Junichi
    2018 9TH INTERNATIONAL CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY (ICAST), 2018, : 167 - 174
  • [6] Users' Fuzzy Cognition Knowledge Learning In Interactive Evolutionary Computation and Its Application
    Hao, Guo-Sheng
    Zaho, Xiang-Jun
    Huang, Yong-Qing
    ADVANCED RESEARCH ON INDUSTRY, INFORMATION SYSTEMS AND MATERIAL ENGINEERING, PTS 1-7, 2011, 204-210 : 245 - +
  • [7] Interactive Evolutionary Computation System with User Gaze Information
    Takenouchi, Hiroshi
    Tokumaru, Masataka
    INTERNATIONAL JOURNAL OF AFFECTIVE ENGINEERING, 2019, 18 (03): : 109 - 116
  • [8] Interactive evolutionary computation system with additional and forgetting learning
    Furuta, Hitoshi
    Hasegawa, Tomokazu
    Fukuhara, Saeri
    CJK-OSM 4: THE FOURTH CHINA-JAPAN-KOREA JOINT SYMPOSIUM ON OPTIMIZATION OF STRUCTURAL AND MECHANICAL SYSTEMS, 2006, : 659 - 664
  • [9] Development of an Interactive Evolutionary Computation Catalog Interface with User Gaze Information
    Takenouchi, Hiroshi
    Tokumaru, Masataka
    HCI INTERNATIONAL 2018 - POSTERS' EXTENDED ABSTRACTS, PT I, 2018, 850 : 121 - 128
  • [10] Rational user - A sufficient condition for global convergence in interactive evolutionary computation
    School of Computer Science and Technology, Xuzhou Normal University, Xuzhou 221116, China
    不详
    不详
    Moshi Shibie yu Rengong Zhineng, 2008, 4 (441-445):
12345