A model-independent theory of consensus and dissensus decision making
Alessio Franci, Martin Golubitsky, Anastasia Bizyaeva, Naomi Ehrich, Leonard

TL;DR
This paper introduces a model-independent framework for analyzing opinion dynamics in decision-making networks, revealing flexible behaviors like consensus and dissensus without relying on specific models.
Contribution
It develops a general, model-independent approach using equivariant bifurcation theory to study opinion networks with arbitrary agents and options, and proves new theoretical results.
Findings
Reveals flexible opinion-formation behaviors including switching between consensus and dissensus.
Provides a novel analytical model with a sigmoidal nonlinearity.
Uncovers model-independent properties of opinion dynamics.
Abstract
We develop a model-independent framework to study the dynamics of decision-making in opinion networks for an arbitrary number of agents and an arbitrary number of options. Model-independence means that the analysis is not performed on a specific set of equations, in contrast to classical approaches to decision making that fix a specific model and analyze it. Rather, the general features of decision making in dynamical opinion networks can be derived starting from empirically testable hypotheses about the deciding agents, the available options, and the interactions among them. After translating these empirical hypotheses into algebraic ones, we use the tools of equivariant bifurcation theory to uncover model-independent properties of dynamical opinion networks. The model-independent results are illustrated on a novel analytical model that is constructed by plugging a generic sigmoidal…
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