Four Classes of Morphogenetic Collective Systems
Hiroki Sayama

TL;DR
This study explores how different morphogenetic principles influence self-organization in collective systems, demonstrating through simulations that component heterogeneity and information sharing enhance coherent spatial organization.
Contribution
The paper introduces a classification of morphogenetic collective systems based on principles and extends the Swarm Chemistry model to analyze their effects.
Findings
Heterogeneity significantly affects swarm structure and behavior.
Dynamic differentiation promotes spatial coherence.
Information sharing maintains organized swarm formations.
Abstract
We studied the roles of morphogenetic principles---heterogeneity of components, dynamic differentiation/re-differentiation of components, and local information sharing among components---in the self-organization of morphogenetic collective systems. By incrementally introducing these principles to collectives, we defined four distinct classes of morphogenetic collective systems. Monte Carlo simulations were conducted using an extended version of the Swarm Chemistry model that was equipped with dynamic differentiation/re-differentiation and local information sharing capabilities. Self-organization of swarms was characterized by several kinetic and topological measurements, the latter of which were facilitated by a newly developed network-based method. Results of simulations revealed that, while heterogeneity of components had a strong impact on the structure and behavior of the swarms,…
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Taxonomy
TopicsComplex Network Analysis Techniques · Complex Systems and Time Series Analysis
