Efficiency of Information Spreading in a population of diffusing agents

TL;DR

This paper models how information spreads among diffusing agents on a lattice, revealing scaling laws and the impact of information decay, with both numerical and analytical insights into the process.

Contribution

Introduces a novel model for information spreading among diffusing agents, incorporating decay and non-trivial scaling laws, supported by simulations and analytical approximations.

Findings

Spreading time scales as N^{-alpha}L^{beta} with non-integer exponents.

Average information degree I_{av}(z) shows non-monotonic behavior with minima.

Analytical approximations partially recover simulation results.

Abstract

We introduce a model for information spreading among a population of N agents diffusing on a square LxL lattice, starting from an informed agent (Source). Information passing from informed to unaware agents occurs whenever the relative distance is < 1. Numerical simulations show that the time required for the information to reach all agents scales as N^{-alpha}L^{beta}, where alpha and beta are noninteger. A decay factor z takes into account the degeneration of information as it passes from one agent to another; the final average degree of information of the population, I_{av}(z), is thus history-dependent. We find that the behavior of I_{av}(z) is non-monotonic with respect to N and L and displays a set of minima. Part of the results are recovered with analytical approximations.