samjsnn/Physarum-Transport-Network

An interactive transport network simulation inspired by the behaviour of Physarum polycephalum, a slime mold known for its ability to form efficient networks.

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updated Apr 3, 2024

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Physarium Transport Network Visualization

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Oct 3, 2026

README

Physarum-Polycephalum-Network-Simulation

The simulation: https://samjsnn.github.io/Physarum-Transport-Network/

Physarum Polycephalum is a unicellular organism that exhibits swarm like intelligence in it's ability to form efficient food networks. The goal of this project is to demonstrate how interactions at a micro level lead to the complex emergent behaviours observed in real slime molds.

gif4b

The core functionality of the simulation is mimicking the protoplasmic trails of Physarum Polycephalum. Agents within the simulation represent parts of the slime mold moving and interacting to form networks. The behaviour of these agents is regulated by three key parameters:

  • Sensory Angle: Determines the breadth of each agent's sensory perception, influencing its ability to detect environmental stimuli and trail pheromones.

  • Sensory Offset: Defines the distance ahead of each agent where it senses its environment. This parameter plays a crucial role in the direction and movement of the agent.

  • Turn Angle: Influences the agent's ability to turn and change direction in response to the detected stimuli, allowing for dynamic navigation and network formation.

In addition to agent parameters the simulation environment is controlled by two main factors:

  • Diffusion Rate: Affects the spread of pheromone trails left by agents. Higher diffusion rates lead to wider and more dispersed trails, influencing the likelihood of other agents encountering and following these trails.

  • Evaporation Rate: Determines the longevity of the pheromone trails. Faster evaporation rates result in shorter-lived trails, requiring agents to constantly explore and adapt to new paths, avoiding reliance on outdated information.

secondgif smallgif gif3

You can interact with the simulation in real time to see how changes in parameters affect network formation.

The controls are:

  • A/S: Adjust Sensory Angle

  • O/P: Adjust Sensory Offset

  • T/Y: Adjust Turn Angle

  • D/F: Adjust Diffusion Rate

  • E/R: Adjust Evaporation Rate

The sensors are quite straightforward and work as such:

sage jenson

(illustration by Sage Jenson)

samjsnn/Physarum-Transport-Network

An interactive transport network simulation inspired by the behaviour of Physarum polycephalum, a slime mold known for its ability to form efficient networks.

JavaScript

2

44 commits

updated Apr 3, 2024

See the code

See what people are saying

SourceMessageScoreDate

Physarium Transport Network Visualization

2

Oct 3, 2026

README

Physarum-Polycephalum-Network-Simulation

The simulation: https://samjsnn.github.io/Physarum-Transport-Network/

Physarum Polycephalum is a unicellular organism that exhibits swarm like intelligence in it's ability to form efficient food networks. The goal of this project is to demonstrate how interactions at a micro level lead to the complex emergent behaviours observed in real slime molds.

gif4b

The core functionality of the simulation is mimicking the protoplasmic trails of Physarum Polycephalum. Agents within the simulation represent parts of the slime mold moving and interacting to form networks. The behaviour of these agents is regulated by three key parameters:

  • Sensory Angle: Determines the breadth of each agent's sensory perception, influencing its ability to detect environmental stimuli and trail pheromones.

  • Sensory Offset: Defines the distance ahead of each agent where it senses its environment. This parameter plays a crucial role in the direction and movement of the agent.

  • Turn Angle: Influences the agent's ability to turn and change direction in response to the detected stimuli, allowing for dynamic navigation and network formation.

In addition to agent parameters the simulation environment is controlled by two main factors:

  • Diffusion Rate: Affects the spread of pheromone trails left by agents. Higher diffusion rates lead to wider and more dispersed trails, influencing the likelihood of other agents encountering and following these trails.

  • Evaporation Rate: Determines the longevity of the pheromone trails. Faster evaporation rates result in shorter-lived trails, requiring agents to constantly explore and adapt to new paths, avoiding reliance on outdated information.

secondgif smallgif gif3

You can interact with the simulation in real time to see how changes in parameters affect network formation.

The controls are:

  • A/S: Adjust Sensory Angle

  • O/P: Adjust Sensory Offset

  • T/Y: Adjust Turn Angle

  • D/F: Adjust Diffusion Rate

  • E/R: Adjust Evaporation Rate

The sensors are quite straightforward and work as such:

sage jenson

(illustration by Sage Jenson)

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