Swarming collapse under limited information flow between individuals

TL;DR

This paper investigates how limited information flow between individuals affects collective decision-making and swarming behavior, revealing a phase transition that depends on network topology and information capacity.

Contribution

It introduces a combined network, control, and information-theoretic framework to analyze the impact of communication bottlenecks on swarming dynamics, identifying critical data rates for effective collective behavior.

Findings

Swarming effectiveness depends on a minimum information data rate.

Decreasing data rate leads to a second-order phase transition in behavior.

Transition predictions align with information-theoretic models.

Abstract

The emergence of collective decision in swarms and their coordinated response to complex environments underscore the central role played by social transmission of information. Here, the different possible origins of information flow bottlenecks are identified. Using a combination of network-, control- and information-theoretic elements applied to a group of interacting self-propelled particles, the effect of varying information capacity of the signaling channel on dynamic collective behaviors is revealed. We find a sufficient condition on the information data rate that guarantees the effectiveness of swarming while also highlighting the profound connection with the topology of the underlying interaction network. We also show that when decreasing the data rate, the swarming behavior invariably vanishes following a second-order phase transition irrespective of the intrinsic noise level. The variations along the transition line are found to be in good agreement with information-theoretic predictions.