Human opinion dynamics: An inspiration to solve complex optimization problems

被引:26
|
作者
Kaur, Rishemjit [1 ,2 ]
Kumar, Ritesh [1 ,2 ]
Bhondekar, Amol P. [1 ,2 ]
Kapur, Pawan [1 ,2 ]
机构
[1] CSIR, Cent Sci Instruments Org, Chandigarh, India
[2] Acad Sci & Innovat Res, New Delhi, India
来源
SCIENTIFIC REPORTS | 2013年 / 3卷
关键词
SOCIAL IMPACT THEORY;
D O I
10.1038/srep03008
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Human interactions give rise to the formation of different kinds of opinions in a society. The study of formations and dynamics of opinions has been one of the most important areas in social physics. The opinion dynamics and associated social structure leads to decision making or so called opinion consensus. Opinion formation is a process of collective intelligence evolving from the integrative tendencies of social influence with the disintegrative effects of individualisation, and therefore could be exploited for developing search strategies. Here, we demonstrate that human opinion dynamics can be utilised to solve complex mathematical optimization problems. The results have been compared with a standard algorithm inspired from bird flocking behaviour and the comparison proves the efficacy of the proposed approach in general. Our investigation may open new avenues towards understanding the collective decision making.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Human opinion dynamics: An inspiration to solve complex optimization problems
    Rishemjit Kaur
    Ritesh Kumar
    Amol P. Bhondekar
    Pawan Kapur
    [J]. Scientific Reports, 3
  • [2] A new approach to solve opinion dynamics on complex networks
    Wang, Wen-Ting
    He, Yu-Lin
    Huang, Joshua Zhexue
    Ma, Li-Heng
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2020, 145
  • [3] Human behavior-based optimization: a novel metaheuristic approach to solve complex optimization problems
    Seyed-Alireza Ahmadi
    [J]. Neural Computing and Applications, 2017, 28 : 233 - 244
  • [4] Human behavior-based optimization: a novel metaheuristic approach to solve complex optimization problems
    Ahmadi, Seyed-Alireza
    [J]. NEURAL COMPUTING & APPLICATIONS, 2017, 28 : S233 - S244
  • [5] Agent Swarm Optimization: A Platform to Solve Complex Optimization Problems
    Montalvo, I.
    Izquierdo, J.
    Herrera, M.
    Perez, R.
    [J]. PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY, 2010, 94
  • [6] Using Reserves of Computing Optimization to Solve Complex Problems
    V. K. Zadiraka
    [J]. Cybernetics and Systems Analysis, 2019, 55 : 40 - 54
  • [7] STOCHASTIC OPTIMIZATION - EFFICIENT ALGORITHMS TO SOLVE COMPLEX PROBLEMS
    DEGROOT, C
    WURTZ, D
    HANF, M
    HOFFMANN, KH
    PEIKERT, R
    KOLLER, T
    [J]. LECTURE NOTES IN CONTROL AND INFORMATION SCIENCES, 1992, 180 : 546 - 555
  • [8] USING RESERVES OF COMPUTING OPTIMIZATION TO SOLVE COMPLEX PROBLEMS
    Zadiraka, V. K.
    [J]. CYBERNETICS AND SYSTEMS ANALYSIS, 2019, 55 (01) : 40 - 54
  • [9] May Inspiration from the Past Solve the Problems of the Present?
    Pourmand, Mohammad
    Rashedi, Jalil
    Mahdavi Poor, Behroz
    Asgharzadeh, Mohammad
    [J]. IRANIAN JOURNAL OF PUBLIC HEALTH, 2016, 45 (01) : 118 - 119
  • [10] SOLVE COMPLEX SETUP PROBLEMS
    SWENSON, R
    [J]. ELECTRONIC DESIGN, 1995, 43 (22) : 106 - 106