From Disorder to Design: Entropy-Driven Self-Organization in an Agent Based Swarming Model and Pattern Formation

This letter seeks to illuminate the profound connection between complexity, self-organization, emergent behaviour, pattern formation, and entropy concepts that are foundational to understanding our universe. By examining these ideas through the lenses of physics, information theory, and nonlinear dynamics, we uncover a fascinating narrative. Starting with a random cluster of particles possessing distinct internal properties, we activate their interactions and observe the emergence of intricate patterns over time. This journey reveals a transition from unlikely to more probable states. At extreme parameter values, the system showcases stunning patterns and turbulent motions remarkable emergent behaviour propelled by entropy and the dynamic exchange of mutual information. Engaging with probability theory helps us to unveil this intricate connectivity, demonstrating not only its significance but also its potential to reshape our understanding of complex systems.

Publication Details

Journal
ArXiv.org
Published
2025-03-24
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Disorder to Design: Entropy-Driven Self-Organization in an Agent Based Swarming Model and Pattern Formation

ArXiv.org
Modular Robots and Swarm Intelligence
article

From Disorder to Design: Entropy-Driven Self-Organization in an Agent Based Swarming Model and Pattern Formation

article en

Abstract

This letter seeks to illuminate the profound connection between complexity, self-organization, emergent behaviour, pattern formation, and entropy concepts that are foundational to understanding our universe. By examining these ideas through the lenses of physics, information theory, and nonlinear dynamics, we uncover a fascinating narrative. Starting with a random cluster of particles possessing distinct internal properties, we activate their interactions and observe the emergence of intricate patterns over time. This journey reveals a transition from unlikely to more probable states. At extreme parameter values, the system showcases stunning patterns and turbulent motions remarkable emergent behaviour propelled by entropy and the dynamic exchange of mutual information. Engaging with probability theory helps us to unveil this intricate connectivity, demonstrating not only its significance but also its potential to reshape our understanding of complex systems.

ArXiv.org
Reduced inequalities
Openalex Percentile: Top 53%
Modular Robots and Swarm Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.