The Emergence of Habitual Turnout Behavior from an Adaptive Learning Model

Among different kinds of adaptive learning models, a specific kind of aspiration-based adaptive rule suggested by Fowler (2006) is known to generate habitual voters/abstainers. This result is quite interesting in the sense that a “conditional” reinforcement learning rule can produce habitual behavior, which is often explained as product of “unconditional” reinforcement learning. Nevertheless, it has not thoroughly enough been investigated why the adaptive rule can generate habitual behavior. This paper fills this research gap by observing the simulation results in more details. The simulation models are based on a most simple voter turnout game with two different candidates. One of the most important results is that the adaptive rules tend to generate two distinct phases: one-sided competition and close race. This, in turn, results in different types of voters. For composition of different phases in the whole time period, the speed of adaptive learning has a crucial impact, which also affect the proportion of habitual behavior. Based on these results, this paper suggests empirically testable hypotheses.