Mechanisms Inducing Parallel Computation in a Model of Physarum polycephalum Transport Networks

TL;DR

This paper explores how various low-level mechanisms in a multi-agent model of Physarum polycephalum can induce network formation and adaptation, shedding light on programming spatially distributed unconventional computing systems.

Contribution

It catalogs and analyzes intrinsic and environmental mechanisms that induce network behaviors in a Physarum model, advancing understanding of programmable biological and artificial networks.

Findings

Mechanisms induce concurrent chemoattractant and chemorepellent gradient integration.

Nutrient consumption modulates chemoattractant gradients, enabling spatial computation.

The mechanisms facilitate growth, movement, and network minimization in the model.

Abstract

P. polycephalum may be considered as a spatially represented parallel unconventional computing substrate, but how can this `computer' be programmed? In this paper we examine and catalogue individual low-level mechanisms which may be used to induce network formation and adaptation in a multi-agent model of P. polycephalum. These mechanisms include those intrinsic to the model (particle sensor angle, rotation angle, and scaling parameters) and those mediated by the environment (stimulus loca- tion, distance, angle, concentration, engulfment and consumption of nutrients, and the presence of simulated light irradiation, repellents and obstacles). The mechanisms in- duce a concurrent integration of chemoattractant and chemorepellent gradients diffusing within the 2D lattice upon which the agent population resides, stimulating growth, move- ment, morphological adaptation and network minimisation. Chemoattractant gradients, and their modulation by the engulfment and consumption of nutrients by the model population, represent an efficient outsourcing of spatial computation. The mechanisms may prove useful in understanding the search strategies and adaptation of distributed organisms within their environment, in understanding the minimal requirements for com- plex adaptive behaviours, and in developing methods of spatially programming parallel unconventional computers and robotic devices.