Anomalous slowing down of individual human activity due to successive decision-making processes

Abstract

Motivated by a host of empirical evidences revealing the bursty character of human dynamics, we develop a model of human activity based on successive switching between an hesitation state and a decision-realization state, with residency times in the hesitation state distributed according to a heavy-tailed Pareto distribution. This model is particularly reminiscent of an individual strolling through a randomly distributed human crowd. Using a stochastic model based on the concept of anomalous and non-Markovian L\'evy walk, we show exactly that successive decision-making processes drastically slow down the progression of an individual faced with randomly distributed obstacles. Specifically, we prove exactly that the average displacement exhibits a sublinear scaling with time that finds its origins in: (i) the intrinsically non-Markovian character of human activity, and (ii) the power law distribution of hesitation times.