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

## TL;DR

This paper models human activity as alternating between hesitation and decision states with heavy-tailed waiting times, revealing that successive decision processes cause a significant slowdown in movement, characterized by sublinear displacement growth.

## Contribution

It introduces a stochastic model combining non-Markovian Lévy walks and heavy-tailed hesitation times to explain slowed human movement in complex environments.

## Key findings

- Successive decision-making causes sublinear displacement scaling.
- Heavy-tailed hesitation times lead to anomalous slowing down.
- The model captures bursty and hindered human dynamics.

## 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.