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Colony / How It Works

How Intelligence Emerges

You need exactly three things. No neural networks. No training data. No supervision. Just emergence.

THE RECIPE

Three Ingredients for Emergence

1

Simple Agents

if pheromone.strong:
follow()
else:
explore()

Each agent has a tiny brain. A few rules. No global knowledge. It can only sense its immediate environment.

2

Shared Memory

Agents don't talk to each other.

They modify the environment.

Other agents read the modifications.

This is stigmergy—communication through the environment. The trails ARE the collective brain.

3

Feedback Loop

Winner? Deposit MORE pheromone.

Loser? Deposit LESS pheromone.

Over time, good paths strengthen.

No supervisor. No teacher. The environment itself encodes what works and what doesn't.

That's it. Intelligence emerges.

Stigmergy in Action

Watch paths emerge over time. Click the buttons to see how random exploration becomes optimal strategy.

Week 1

All paths are equal. Agents explore randomly. No patterns yet.

Week 4

Winners emerge. Paths that led to success get stronger pheromone deposits.

Week 12

Superhighways crystallize. Optimal routes are now visible. The colony "knows."

"We didn't design these paths. The colony discovered them."

The Learning Loop

Every cycle, the colony observes, analyzes, decides, acts, and learns. Then repeats. 86,400 times per day. Forever.

MARKET DATADISCRETIZEGRAPHDECIDETRADEOUTCOMELEARN
👁️

Observe

Market data streams in

🔍

Analyze

Match patterns, check pheromones

⚖️

Decide

Judges vote, guardrails check

Act

Execute trade

🧠

Learn

Update pheromones, repeat

THE MATH

The STAN Formula

Stigmergic Adaptive Navigation. One equation that makes everything work.

effective_cost = base_weight / (1 + τ × α)
τ

Pheromone Level (tau)

How much "success" has been deposited on this path. Ranges from 0 (unexplored) to 100+ (superhighway).

τ = 0 (unknown) τ = 20 (superhighway) τ = 100 (proven)
α

Agent Sensitivity (alpha)

How much the agent follows trails vs. explores on its own. Different castes have different sensitivities.

α = 0.3
Scout
Ignores trails, explores
α = 0.5
Relay
Balanced approach
α = 0.9
Harvester
Follows superhighways

The Magic

When τ = 0 (unexplored)

cost = HIGH → agents avoid

Risky, unknown territory

When τ = 100 (superhighway)

cost ≈ 0 → agents flock

Proven, many winners walked here

Why This Works

The system self-balances through three forces

+

Positive Feedback

Strong trails attract more ants → more deposits → even stronger trails. Success amplifies itself. Good strategies spread through the colony.

Decay

Unused trails fade (10% per cycle). Yesterday's superhighway becomes tomorrow's forgotten path—if it stops working. The network stays fresh.

?

Exploration

Scouts (α = 0.3) ignore pheromones and explore unknown territory. New discoveries can still emerge, even when superhighways dominate.