Optimized reduction of uncertainty in bursty human dynamics

TL;DR

This paper introduces an agent-based model to understand how humans reduce uncertainty through communication, revealing that optimal waiting times lead to bursty, heavy-tailed dynamics influenced by efficiency and uncertainty levels.

Contribution

It presents a novel agent-based framework linking uncertainty reduction to bursty human communication patterns, highlighting the role of optimal waiting times.

Findings

Optimal waiting times follow a heavy-tailed distribution.

Communication efficiency influences the scaling behavior of waiting times.

Cost relevance varies with uncertainty and efficiency levels.

Abstract

Human dynamics is known to be inhomogeneous and bursty but the detailed understanding of the role of human factors in bursty dynamics is still lacking. In order to investigate their role we devise an agent-based model, where an agent in an uncertain situation tries to reduce the uncertainty by communicating with information providers while having to wait time for responses. Here the waiting time can be considered as cost. We show that the optimal choice of the waiting time under uncertainty gives rise to the bursty dynamics, characterized by the heavy-tailed distribution of optimal waiting time. We find that in all cases the efficiency for communication is relevant to the scaling behavior of the optimal waiting time distribution. On the other hand the cost turns out in some cases to be irrelevant depending on the degree of uncertainty and efficiency.