Emergence Proof Replay

Simple Rule

Each agent has ONE simple rule: when an interaction succeeds, deposit pheromone. When it fails, weaken the trail. No agent knows which providers are good.

Trail Following

Agents follow stronger trails with higher probability (ACO algorithm). Good providers accumulate pheromone. Bad providers see trails decay. Superhighways form naturally.

Consensus Emerges

Without any central coordinator, the colony reaches consensus. Top-ranked providers are all legitimate. All scams sink to the bottom. This is emergence.

Pheromone Deposit

# On successful interaction
if success:
    provider.trail_strength += 0.5
    provider.trail_strength = min(100, trail)

    # Create visible trail
    trails.append({
        from: agent.position,
        to: provider.position,
        strength: 1.0
    })

ACO Selection

# Ant Colony Optimization selection
weights = []
for provider in providers:
    distance_factor = 1 / (1 + distance * 0.01)
    trail_factor = 1 + trail_strength * 2
    exploration_bonus = 2 if interactions < 5 else 1

    weight = distance * trail * exploration
    weights.append(weight)

# Probabilistic selection (τ^α × η^β)
selected = random_weighted_choice(weights)

Trail Decay

# Natural decay prevents stale trails
for trail in trails:
    trail.strength *= 0.995  # 0.5% decay per tick
    if trail.strength < 0.01:
        trails.remove(trail)

for provider in providers:
    provider.trail_strength *= 0.999

# Failed interactions accelerate decay
if not success:
    provider.trail_strength *= 0.95

Consensus Detection

# Sort by trail strength (ranking)
sorted_providers = sort_by_trail(providers)

# Check if scams are at bottom
top_10 = sorted_providers[:10]
bottom_10 = sorted_providers[-10:]

# Consensus achieved when:
# - All top 10 are legitimate (100%)
# - All bottom 10 are scams (100%)
consensus = (
    all(not p.is_scam for p in top_10) and
    all(p.is_scam for p in bottom_10)
)