Fast-and-flexible decision-making with modulatory interactions

TL;DR

This paper introduces a nonlinear opinion dynamics model with modulatory interactions, enhancing the understanding of decision-making speed, robustness, and flexibility in multi-agent systems across biological and social contexts.

Contribution

It presents a novel nonlinear opinion dynamics model incorporating modulatory interactions, offering new insights into their role in decision-making processes.

Findings

Modulatory interactions significantly enrich decision-making behavior.

The model is mathematically tractable and applicable to biological and social networks.

Provides tools for understanding and engineering decision-making networks.

Abstract

Multi-agent systems in biology, society, and engineering are capable of making decisions through the dynamic interaction of their elements. Nonlinearity of the interactions is key for the speed, robustness, and flexibility of multi-agent decision-making. In this work we introduce modulatory, that is, multiplicative, in contrast to additive, interactions in a nonlinear opinion dynamics model of fast-and-flexible decision-making. The original model is nonlinear because network interactions, although additive, are saturated. Modulatory interactions introduce an extra source of nonlinearity that greatly enriches the model decision-making behavior in a mathematically tractable way. Modulatory interactions are widespread in both biological and social decision-making networks; our model provides new tools to understand the role of these interactions in networked decision-making and to engineer them in artificial systems.