Binary Consensus via Exponential Smoothing
نویسندگان
چکیده
In this paper, we reinterpret the most basic exponential smoothing equation as a model of social influence. Exponential smoothing has been used as a time-series forecasting and data filtering technique since the 1950s. The most basic exponential smoothing equation, S t+1 = (1−α)S +αX, is used to estimate the value of a series at time t+ 1, denoted by S , as a convex combination of the current estimate S and the actual observation of the time series X. In our work, we interpret the variable S as an agent’s tendency to imitate the observed behavior of another agent, which is represented by a binary variable X. We study the dynamics of the resulting system when the agents exhibit a behavior for a period of time, called latency, whose duration is stochastic. 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, a bias is produced. This bias makes all the agents in a population adopt one specific behavior. This phenomenon has applications in domains where it is desired that a group of agents adopts a behavior by consensus.
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