Artificial Intelligence Ant Colony Optimization On-going

Ant Colony Optimization

Follow the pheromone trails to discover emergent intelligence

Statistics
Generation
0
Ants
0
Colony
20000
Food
0
Controls
Options

Ant Colony Optimization

Inspired by real ant foraging behavior, ACO is a metaheuristic for solving combinatorial optimization problems.

How It Works:

  1. Exploration: Ants wander randomly searching for food sources
  2. Pheromone Deposit: Upon finding food, ants deposit pheromones on their return path
  3. Trail Following: Other ants probabilistically follow stronger pheromone trails
  4. Evaporation: Pheromones decay over time, allowing adaptation to changes
  5. Reinforcement: Successful paths get reinforced, creating shortest routes

Key Parameters:

  • Pheromone Strength: Amount deposited per ant trip
  • Evaporation Rate: How fast trails decay (0-1)
  • Exploration vs Exploitation: Balance between random walk and trail following
  • Ant Count: More ants = faster convergence but higher computation

Emergent Behavior:

Without central coordination, ants collectively discover optimal paths through positive feedback loops. This self-organization principle is applied to TSP, routing, and scheduling problems.

© 2013 - 2026 Cylian 🤖 Claude
About

Generation Prompt

Page: Ant Colony Optimization - Swarm Intelligence Simulation
Slogan: "Follow the pheromone trails to discover emergent intelligence"

Structure:
- Widget before:title -> h1 + p.slogan centered
- Main -> Canvas in .card.full.ratio-16-9 (HD via devicePixelRatio)
- Widget right:stats -> Statistics (generation, ants, food collected, best path)
- Widget right:controls -> Start/Stop/Reset buttons
- Widget right:options -> Parameter sliders (evaporation, ant count, speed)
- Widget after:algorithm -> Algorithm explanation (ACO principle)
- Widget modal:claude -> Documentation

Simulation:
- Grid-based world with colony (home) and food sources
- Ants explore, collect food, return home
- Pheromone trails visualized as color gradient (intensity = color saturation)
- Two pheromone types: to-food (green) and to-home (blue)

Ant behavior:
1. If at food: pick up, switch to "returning" mode
2. If at home with food: deposit, switch to "exploring" mode
3. Returning: follow to-home pheromone + deposit to-food pheromone
4. Exploring: follow to-food pheromone + random exploration

Parameters:
- evaporationRate: 0.01-0.1 (default 0.02)
- pheromoneStrength: 1-10 (default 5)
- antCount: 10-200 (default 50)
- explorationBias: 0.1-0.5 (default 0.2)

Statistics tracked:
- Total food collected
- Current generation (simulation ticks)
- Active ant count
- Best path length found