Life Finds A Way: Emergence of Cooperative Structures in Adaptive Threshold Networks
Sean P. Maley, Carlos Gershenson, Stuart A. Kauffman

TL;DR
This paper introduces a novel adaptive threshold network model to study how cooperative and antagonistic interactions influence the emergence of complex organizational structures in biological and economic systems.
Contribution
It presents a new random threshold-directed network model integrating node traits with dynamic edge formation and removal, extending classical network models.
Findings
Higher-order organization emerges despite antagonism.
Qualitative transitions occur with increasing system size.
Model offers insights into community evolution and resilience.
Abstract
There has been a long debate on how new levels of organization have evolved. It might seem unlikely, as cooperation must prevail over competition. One well-studied example is the emergence of autocatalytic sets, which seem to be a prerequisite for the evolution of life. Using a simple model, we investigate how varying bias toward cooperation versus antagonism shapes network dynamics, revealing that higher-order organization emerges even amid pervasive antagonistic interactions. In general, we observe that a quantitative increase in the number of elements in a system leads to a qualitative transition. We present a random threshold-directed network model that integrates node-specific traits with dynamic edge formation and node removal, simulating arbitrary levels of cooperation and competition. In our framework, intrinsic node values determine directed links through various threshold…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Complex Network Analysis Techniques
