Binary consensus via exponential smoothing

Marco A.M. Montes de Oca, Eliseo Ferrante, Alexander Scheidler, Louis F. Rossi

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper, we reinterpret the most basic exponential smoothing equation, St+1 = (1 − α)St + αXt, as a model of social influence. This equation is typically used to estimate the value of a series at time t + 1, denoted by St+1, as a convex combination of the current estimate St and the actual observation of the time series Xt. In our work, we interpret the variable St as an agent’s tendency to adopt the observed behavior or opinion of another agent, which is represented by a binary variable Xt. We study the dynamics of the resulting system when the agents’ recently adopted behaviors or opinions do not change for a period of time of stochastic duration, called latency. Latency allows us to model real-life situations such as product adoption, or action execution. When different latencies are associated with the two different behaviors or opinions, a bias is produced. This bias makes all the agents in a population adopt one specific behavior or opinion. We discuss the relevance of this phenomenon in the swarm intelligence field.

Original languageEnglish
Title of host publicationComplex Sciences - 2nd International Conference, COMPLEX 2012, Revised Selected Papers
EditorsKristin Glass, Richard Colbaugh, Jeffrey Tsao, Paul Ormerod
PublisherSpringer Verlag
Pages244-255
Number of pages12
ISBN (Print)9783319034720
Publication statusPublished - 1 Jan 2013
Externally publishedYes
Event2nd International Conference on Complex Sciences, COMPLEX 2012 - Santa Fe, United States
Duration: 5 Dec 20127 Dec 2012

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume126 LNICST
ISSN (Print)1867-8211

Conference

Conference2nd International Conference on Complex Sciences, COMPLEX 2012
CountryUnited States
CitySanta Fe
Period5/12/127/12/12

Keywords

  • Collective decision-making
  • Consensus
  • Self-Organization
  • Swarm intelligence

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