Cross-inhibition leads to group consensus despite the presence of strongly opinionated minorities and asocial behaviour

TL;DR

This paper demonstrates that cross-inhibition, a common biological mechanism, enables collective decision-making to reach a stable majority despite opinionated minorities and individualistic behavior, validated through robotic experiments.

Contribution

It introduces cross-inhibition as a simple, robust mechanism for collective decisions, contrasting it with existing models and confirming its effectiveness through robotic swarm experiments.

Findings

Cross-inhibition allows stable majority decisions despite opinionated minorities.

Robotic experiments confirm mean-field model predictions.

Cross-inhibition is widespread in natural collective decision systems.

Abstract

Strongly opinionated minorities can have a dramatic impact on the opinion dynamics of a large population. Two factions of inflexible minorities, polarised into two competing opinions, could lead the entire population to persistent indecision. Equivalently, populations can remain undecided when individuals sporadically change their opinion based on individual information rather than social information. Our analysis compares the cross-inhibition model with the voter model for decisions between equally good alternatives, and with the weighted voter model for decisions among alternatives characterised by different qualities. Here we show that cross-inhibition, differently from the other two models, is a simple mechanism, ubiquitous in collective biological systems, that allows the population to reach a stable majority for one alternative even in the presence of asocial behaviour. The results predicted by the mean-field models are confirmed by experiments with swarms of 100 locally interacting robots. This work suggests an answer to the longstanding question of why inhibitory signals are widespread in natural systems of collective decision making, and, at the same time, it proposes an efficient mechanism for designing resilient swarms of minimalistic robots.