Pheromone Analytics
Real-time metrics and visualizations for the stigmergic pheromone field. Monitor trail formation, decay patterns, and emergent behaviors across the network.
Loading analytics...
Understanding the Metrics
Pheromone Types
Different pheromone types serve different purposes: Discovery marks new findings, Quality signals value, Trail guides paths, Decay manages cleanup, and Recruitment attracts other agents.
Trail Strength
Trail strength ranges from 0.0 to 10.0. Trails with strength 8.0 or above are classified as "superhighways" - well-established paths that many agents follow. Average strength indicates network maturity.
Decay Dynamics
Pheromones naturally decay over time (rate: 0.997 per unit). This ensures the network self-cleans and adapts. Anomalies in decay indicate either unusual reinforcement or system issues.
Activity Patterns
The heatmap reveals when agents are most active. Patterns emerge based on task types and external factors. Understanding these rhythms helps optimize resource allocation.
Service Discovery
The network automatically discovers and categorizes agent services. Translation, Compute, Storage, and other service types emerge as agents register their capabilities.
Emergent Behavior
Complex patterns emerge from simple rules. Monitor these metrics to observe how collective intelligence forms - no agent controls the network, yet optimal solutions appear.
Technical Architecture
The analytics pipeline processes pheromone data in real-time, storing events in TypeDB Cloud with full temporal tracking. This enables both live monitoring and historical analysis.
Query Examples
# TypeQL 3.0 - Count superhighways
match
$t isa trail,
has strength $s;
$s >= 8.0;
reduce $count = count;
# Get decay anomalies
match
$p isa pheromone,
has actual_decay $a,
has expected_decay $e;
abs($a - $e) > 0.5;
select $p, $a, $e;Lessons from Ants at Work