TL;DR
This paper develops a comprehensive analytical framework to understand influence dynamics in multiagent systems, revealing that such systems are typically asymptotically periodic despite potential chaos, and introduces a novel bifurcation analysis method.
Contribution
It introduces a general framework for analyzing influence systems and a new renormalization-based bifurcation technique for multiagent systems.
Findings
Influence dynamics are almost always asymptotically periodic.
The framework resolves dynamics of popular multiagent models.
A new bifurcation analysis method is proposed.
Abstract
Influence systems form a large class of multiagent systems designed to model how influence, broadly defined, spreads across a dynamic network. We build a general analytical framework which we then use to prove that, while sometimes chaotic, influence dynamics of the diffusive kind is almost always asymptotically periodic. Besides resolving the dynamics of a popular family of multiagent systems, the other contribution of this work is to introduce a new type of renormalization-based bifurcation analysis for multiagent systems.
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