Convergence properties of the heterogeneous Deffuant-Weisbuch model

被引:37
作者
Chen, Ge [1 ,2 ]
Su, Wei [3 ]
Mei, Wenjun [4 ]
Bullo, Francesco [5 ,6 ]
机构
[1] Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
[2] Chinese Acad Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing 100190, Peoples R China
[3] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
[4] ETH, Automat Control Lab, CH-8092 Zurich, Switzerland
[5] Univ Calif Santa Barbara, Dept Mech Engn, Santa Barbara, CA 93106 USA
[6] Univ Calif Santa Barbara, Ctr Control Dynam Syst & Computat, Santa Barbara, CA 93106 USA
基金
中国国家自然科学基金;
关键词
Opinion dynamics; Consensus; Deffuant model; Gossip model; Bounded confidence model; CONTINUOUS OPINION DYNAMICS; CONFIDENCE; TUTORIAL;
D O I
10.1016/j.automatica.2020.108825
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Deffuant-Weisbuch (DW) model is a bounded-confidence opinion dynamics model that has attracted much recent interest. Despite its simplicity and appeal, the DW model has proved technically hard to analyze and its most basic convergence properties, easy to observe numerically, are only conjectures. This paper solves the convergence problem for the heterogeneous DW model with the weighting factor not less than 1/2. We establish that, for any positive confidence bounds and initial values, the opinion of each agent will converge to a limit value almost surely, and the convergence rate is exponential in mean square. Moreover, we show that the limiting opinions of any two agents either are the same or have a distance larger than the confidence bounds of the two agents. Finally, we provide some sufficient conditions for the heterogeneous DW model to reach consensus. (C) 2020 Elsevier Ltd. All rights reserved.
引用
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页数:9
相关论文
共 25 条
  • [1] [Anonymous], 1959, Studies in social power
  • [2] Randomized gossip algorithms
    Boyd, Stephen
    Ghosh, Arpita
    Prabhakar, Balaji
    Shah, Devavrat
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 2006, 52 (06) : 2508 - 2530
  • [3] Bullo F., 2019, LECT NETWORK SYSTEMS
  • [4] Inertial Hegselmann-Krause Systems
    Chazelle, Bernard
    Wang, Chu
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2017, 62 (08) : 3905 - 3913
  • [5] Small Noise May Diversify Collective Motion in Vicsek Model
    Chen, Ge
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2017, 62 (02) : 636 - 651
  • [6] SCALING LIMITS FOR CONTINUOUS OPINION DYNAMICS SYSTEMS
    Como, Giacomo
    Fagnani, Fabio
    [J]. ANNALS OF APPLIED PROBABILITY, 2011, 21 (04) : 1537 - 1567
  • [7] Mixing beliefs among interacting agents
    Deffuant, G
    Neau, D
    Amblard, F
    Weisbuch, G
    [J]. APPLICATIONS OF SIMULATION TO SOCIAL SCIENCES, 2000, : 87 - 98
  • [8] REACHING A CONSENSUS
    DEGROOT, MH
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1974, 69 (345) : 118 - 121
  • [9] A FORMAL THEORY OF SOCIAL POWER
    FRENCH, JRP
    [J]. PSYCHOLOGICAL REVIEW, 1956, 63 (03) : 181 - 194
  • [10] Friedkin N., 1998, A structural theory of social influence