Application to AI Ant Colony
Translating biology to code
From Biology to Code
Biological principles translate to digital systems through functional equivalences, not mechanism copying. We don't simulate pheromones - we implement their function.
The STAN algorithm embodies stigmergic optimization: Sense, Think, Act, Navigate.
Functional Equivalences
Ground and surfaces become TypeDB entities. Pheromones become intensity values on edges. Trails become weighted paths. Evaporation becomes decay functions.
- Physical trails = Graph edges with weights
- Pheromone deposit = Weight increase
- Evaporation = Scheduled decay
- Antenna sensing = Graph queries
Caste Differentiation
Like ant castes, our agents have different behavioral parameters. Scouts have low pheromone sensitivity (explore). Harvesters have high sensitivity (exploit).
Castes emerge through selection pressure, not top-down design.
Key Concepts
"The key is to understand the function, not copy the mechanism."
Summary
Biological principles translate to digital systems through functional equivalences, not mechanism copying. The STAN algorithm embodies stigmergic optimization: pheromones reduce effective path cost, creating positive feedback for successful strategies.
Lessons from Ants at Work