TY - GEN
T1 - Opinion formation under bounded confidence via gossip algorithms
AU - Thi Hoai Linh, Nguyen
AU - Wada, Takayuki
AU - Masubuchi, Izumi
AU - Asai, Toru
AU - Fujisaki, Yasumasa
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/2/8
Y1 - 2015/2/8
N2 - This paper investigates two bounded confidence gossip algorithms, one with constant confidence threshold and the other with increasing one, for effective communicating between agents in a network among whom some opinion formation forms. Each agent in the network keeps a real value presenting its opinion about some matter. The opinions of agents will be updated time by time according to an iterative procedure. At each time, (i) two arbitrary agents are chosen randomly, (ii) they exchange their opinions, and (iii) if the distance between the opinions does not exceed some given confidence threshold, they update their opinions as the average of the two. It is shown that the algorithms almost surely drive any initial opinion profile to some opinion profile in which any two opinions either are the same or differ more than the confidence threshold. Moreover, the second algorithm can help achieving a prescribed number of different opinions on the convergence opinion profiles.
AB - This paper investigates two bounded confidence gossip algorithms, one with constant confidence threshold and the other with increasing one, for effective communicating between agents in a network among whom some opinion formation forms. Each agent in the network keeps a real value presenting its opinion about some matter. The opinions of agents will be updated time by time according to an iterative procedure. At each time, (i) two arbitrary agents are chosen randomly, (ii) they exchange their opinions, and (iii) if the distance between the opinions does not exceed some given confidence threshold, they update their opinions as the average of the two. It is shown that the algorithms almost surely drive any initial opinion profile to some opinion profile in which any two opinions either are the same or differ more than the confidence threshold. Moreover, the second algorithm can help achieving a prescribed number of different opinions on the convergence opinion profiles.
UR - http://www.scopus.com/inward/record.url?scp=84962030761&partnerID=8YFLogxK
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U2 - 10.1109/CDC.2015.7402537
DO - 10.1109/CDC.2015.7402537
M3 - Conference contribution
AN - SCOPUS:84962030761
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 2223
EP - 2228
BT - 54rd IEEE Conference on Decision and Control,CDC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 54th IEEE Conference on Decision and Control, CDC 2015
Y2 - 15 December 2015 through 18 December 2015
ER -