A Survey on Physarum Polycephalum Intelligent Foraging Behaviour and Bio-Inspired Applications

TL;DR

This paper provides a comprehensive review of Physarum polycephalum's biological behavior, mathematical models, and bio-inspired algorithms, emphasizing recent advances and introducing a new competition-based simulation model with promising future research potential.

Contribution

It offers a novel exploration of Physarum's intelligent behavior in competitive settings and presents a new model for simulating Physarum interactions.

Findings

Physarum-inspired algorithms effectively solve NP-hard problems.

The new competition model simulates Physarum interactions realistically.

Bio-inspired algorithms show great potential for future applications.

Abstract

In recent years, research on Physarum polycephalum has become more popular after Nakagaki et al. (2000) performed their famous experiment showing that Physarum was able to find the shortest route through a maze. Subsequent researches have confirmed the ability of Physarum-inspired algorithms to solve a wide range of NP-hard problems. In contrast to previous reviews that either focus on biological aspects or bio-inspired applications, here we present a comprehensive review that highlights recent Physarum polycephalum biological aspects, mathematical models, and Physarum bio-inspired algorithms and their applications. The novelty of this review stems from our exploration of Physarum intelligent behaviour in competition settings. Further, we have presented our new model to simulate Physarum in competition, where multiple Physarum interact with each other and with their environments. The bio-inspired Physarum in competition algorithms proved to have great potentials for future research.