Ant Simulator

A simple Python simulation that models ant colony behavior using pheromone-based pathfinding.

Overview

This project simulates ants searching for food, depositing pheromones, and following trails to optimize their routes over time. Each ant acts as an independent agent with behaviors such as exploring, carrying food, and returning to the nest.

Features

• Pheromone-based pathfinding to simulate trail optimization
• Agent behaviors including food collection and nest navigation
• Real-time visualization of ant movement and pheromone diffusion

Technologies Used

• Python

Purpose

• Built to explore swarm intelligence concepts and emergent behavior in multi-agent systems.