Ant Droplet Dynamics Evolve via Individual Decision-Making

Research output: Contribution to journalArticle

Abstract

The droplets of a set of ants were studied while they constructed a bridge. A droplet is a group of ants derived from a larger group. Several experimental studies have revealed the droplet dynamics of ants that resemble the self-organising characteristics that are displayed in their physico-chemical systems. However, little is known regarding how these typical behaviours emerge from individual decision-making. In this study, I developed an agent-based model where artificial ants aggregated, thereby resulting in chain and droplet growth. In my proposed model, the agents tuned their weight thresholds according to the local pattern stability and propagation of negative information. As a result, it was revealed that the droplet dynamics of my proposed model partly matched the time series of droplets of real ants, as demonstrated in previous experimental studies that included the fluctuation function and interdrop increments that followed a scale-free distribution.

Original languageEnglish
Article number14877
JournalScientific Reports
Volume7
Issue number1
DOIs
Publication statusPublished - Dec 1 2017

Fingerprint

Decision making
Time series

ASJC Scopus subject areas

  • General

Cite this

Ant Droplet Dynamics Evolve via Individual Decision-Making. / Sakiyama, Tomoko.

In: Scientific Reports, Vol. 7, No. 1, 14877, 01.12.2017.

Research output: Contribution to journalArticle

@article{ebd6fd4fabc048c1aba53a507c070374,
title = "Ant Droplet Dynamics Evolve via Individual Decision-Making",
abstract = "The droplets of a set of ants were studied while they constructed a bridge. A droplet is a group of ants derived from a larger group. Several experimental studies have revealed the droplet dynamics of ants that resemble the self-organising characteristics that are displayed in their physico-chemical systems. However, little is known regarding how these typical behaviours emerge from individual decision-making. In this study, I developed an agent-based model where artificial ants aggregated, thereby resulting in chain and droplet growth. In my proposed model, the agents tuned their weight thresholds according to the local pattern stability and propagation of negative information. As a result, it was revealed that the droplet dynamics of my proposed model partly matched the time series of droplets of real ants, as demonstrated in previous experimental studies that included the fluctuation function and interdrop increments that followed a scale-free distribution.",
author = "Tomoko Sakiyama",
year = "2017",
month = "12",
day = "1",
doi = "10.1038/s41598-017-13775-5",
language = "English",
volume = "7",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",

}

TY - JOUR

T1 - Ant Droplet Dynamics Evolve via Individual Decision-Making

AU - Sakiyama, Tomoko

PY - 2017/12/1

Y1 - 2017/12/1

N2 - The droplets of a set of ants were studied while they constructed a bridge. A droplet is a group of ants derived from a larger group. Several experimental studies have revealed the droplet dynamics of ants that resemble the self-organising characteristics that are displayed in their physico-chemical systems. However, little is known regarding how these typical behaviours emerge from individual decision-making. In this study, I developed an agent-based model where artificial ants aggregated, thereby resulting in chain and droplet growth. In my proposed model, the agents tuned their weight thresholds according to the local pattern stability and propagation of negative information. As a result, it was revealed that the droplet dynamics of my proposed model partly matched the time series of droplets of real ants, as demonstrated in previous experimental studies that included the fluctuation function and interdrop increments that followed a scale-free distribution.

AB - The droplets of a set of ants were studied while they constructed a bridge. A droplet is a group of ants derived from a larger group. Several experimental studies have revealed the droplet dynamics of ants that resemble the self-organising characteristics that are displayed in their physico-chemical systems. However, little is known regarding how these typical behaviours emerge from individual decision-making. In this study, I developed an agent-based model where artificial ants aggregated, thereby resulting in chain and droplet growth. In my proposed model, the agents tuned their weight thresholds according to the local pattern stability and propagation of negative information. As a result, it was revealed that the droplet dynamics of my proposed model partly matched the time series of droplets of real ants, as demonstrated in previous experimental studies that included the fluctuation function and interdrop increments that followed a scale-free distribution.

UR - http://www.scopus.com/inward/record.url?scp=85032840889&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85032840889&partnerID=8YFLogxK

U2 - 10.1038/s41598-017-13775-5

DO - 10.1038/s41598-017-13775-5

M3 - Article

VL - 7

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 14877

ER -