Swarms, Phase Transitions, and Collective Intelligence

TL;DR

This paper introduces a spatially extended model of collective behavior in organisms, focusing on phase transitions and self-organization, with a specific application to ant movement inspired by laboratory observations.

Contribution

The paper presents a novel model linking morphogen dynamics and organism movement, demonstrating phase transitions and self-organization in collective biological systems, validated against experimental data.

Findings

Model exhibits various phase transitions controlled by noise and parameters.

Analytic results align with laboratory observations of ant behavior.

Model serves as a paradigm for complex cooperative systems in nature.

Abstract

A spacially extended model of the collective behavior of a large number of locally acting organisms is proposed in which organisms move probabilistically between local cells in space, but with weights dependent on local morphogenetic substances, or morphogens. The morphogens are in turn are effected by the passage of an organism. The evolution of the morphogens, and the corresponding flow of the organisms constitutes the collective behavior of the group. Such models have various types of phase transitions and self-organizing properties controlled both by the level of the noise, and other parameters. The model is then applied to the specific case of ants moving on a lattice. The local behavior of the ants is inspired by the actual behavior observed in the laboratory, and analytic results for the collective behavior are compared to the corresponding laboratory results. It is hoped that the present model might serve as a paradigmatic example of a complex cooperative system in nature. In particular swarm models can be used to explore the relation of nonequilibrium phase transitions to at least three important issues encountered in artificial life. Firstly, that of emergence as complex adaptive behavior. Secondly, as an exploration of continuous phase transitions in biological systems. Lastly, to derive behavioral criteria for the evolution of collective behavior in social organisms.