An interactive, browser-based simulation of an ant colony that evolves over time using a genetic algorithm. This project was built with p5.js and demonstrates concepts of emergent behavior, natural selection, and environmental adaptation.
This simulation creates a dynamic ecosystem where a colony of ants must survive and thrive. Each ant has a unique set of genes that determine its traits, such as speed, size, and sensory range. The colony faces challenges like finding food, navigating obstacles, and defending against predators. Through a process of natural selection, the genetic makeup of the colony evolves to better adapt to its environment.
- Genetic Algorithm: Ants pass on their genes to the next generation with a chance of mutation. Successful traits are naturally selected for, leading to an evolving colony.
- Emergent Behavior: Complex colony-level strategies, like efficient foraging paths, emerge from the simple rules governing individual ants and their pheromone trails.
- Specialized Ant Roles: The colony is composed of different types of ants—Workers, Soldiers, and Scouts—each with distinct behaviors and genetic predispositions, creating a natural division of labor.
- Dynamic Environment: The world is procedurally generated with obstacles, food sources, and predator nests, ensuring that each simulation run is unique.
- Real-time Data Visualization: The simulation includes interactive graphs that display the colony's population dynamics and the evolution of key genetic traits over time.
- p5.js - The core JavaScript library for creative coding.
- HTML5 & CSS3
To run this simulation on your local machine, you can simply download the repository and open the index.html file in your web browser.
You will need a modern web browser that supports HTML5 and JavaScript.
- Clone the repo
git clone https://github.com/NeoLorenzo/Ant-Colony-Genetic-Simulation.git
- Navigate to the project directory and open
index.htmlin your browser.
The simulation loop continuously updates the state of each ant and the environment.
- Ants' Behavior: Each ant makes decisions based on its current state (e.g., carrying food, seeking food), its role, and the pheromone trails it senses.
- Pheromones: Ants leave behind "home" and "food" pheromones. These trails evaporate and diffuse over time, guiding other ants. "Danger" pheromones are dropped when predators are encountered.
- Reproduction: The colony reproduces by spending "reproduction energy" gathered from food. New ants inherit a mix of genes from two parent ants, with a chance of mutation. The parents are chosen based on their success (e.g., how much food a worker has gathered).
- Predators: Predators spawn and hunt ants, creating selective pressure on the colony, particularly favoring stronger soldiers and more cautious workers and scouts.
Project Link: https://github.com/NeoLorenzo/Ant-Colony-Genetic-Simulation