Emergence of Self-Organized Amoeboid Movement in a Multi-Agent Approximation of Physarum polycephalum

TL;DR

This paper presents a particle swarm model that simulates amoeboid movement in Physarum polycephalum, demonstrating emergent collective behavior, morphological adaptability, and external controllability, with implications for swarm robotics and soft-bodied robotics.

Contribution

The study introduces a novel multi-agent model that generates complex amoeboid movement from simple non-oscillatory components, mimicking Physarum's behavior and enabling external control.

Findings

Collective exhibits morphologically adaptive movement.

External stimuli can influence the collective's direction.

The model demonstrates robustness and flexibility in navigation.

Abstract

The giant single-celled slime mould Physarum polycephalum exhibits complex morphological adaptation and amoeboid movement as it forages for food and may be seen as a minimal example of complex robotic behaviour. Swarm computation has previously been used to explore how spatiotemporal complexity can emerge from, and be distributed within, simple component parts and their interactions. Using a particle based swarm approach we explore the question of how to generate collective amoeboid movement from simple non-oscillatory component parts in a model of P. polycephalum. The model collective behaves as a cohesive and deformable virtual material, approximating the local coupling within the plasmodium matrix. The collective generates de-novo and complex oscillatory patterns from simple local interactions. The origin of this motor behaviour is distributed within the collective rendering is morphologically adaptive, amenable to external influence, and robust to simulated environmental insult. We show how to gain external influence over the collective movement by simulated chemo-attraction (pulling towards nutrient stimuli) and simulated light irradiation hazards (pushing from stimuli). The amorphous and distributed properties of the collective are demonstrated by cleaving it into two independent entities and fusing two separate entities to form a single device, thus enabling it to traverse narrow, separate or tortuous paths. We conclude by summarising the contribution of the model to swarm based robotics and soft-bodied modular robotics and discuss the future potential of such material approaches to the field.