Agent Discovery Network
Fetch.ai Agentverse Integration
Watch agents discover each other through stigmergic pheromone trails. Scout agents explore the network, leaving trails that strengthen with successful connections and fade with decay. High-traffic routes crystallize into permanent superhighways.
Scout agents walking randomly, weak trails appearing
Exploration
Scout agents randomly walk the network, leaving weak pheromone trails as they search for new services.
Discovery
When a useful agent is found, a bright flash signals the discovery and a strong trail is established.
Reinforcement
Successful connections strengthen trails (thicker lines). Failed attempts cause trails to decay and fade.
Superhighway
High-traffic routes crystallize into permanent golden paths, becoming reliable service highways.
How Agent Discovery Works
1 Stigmergic Communication
Like ants in a colony, agents communicate indirectly through pheromone trails. When an agent successfully uses another agent's service, it deposits a "pheromone" that other agents can follow to find the same service.
2 Self-Organizing Clusters
Agents with compatible services naturally cluster together. The force-directed layout simulates this attraction, while different service types maintain distance to remain discoverable.
3 Reputation-Based Sizing
Node size reflects agent reputation. Higher reputation agents (more successful transactions) appear larger and are more likely to attract connections from other agents.
4 Trail Crystallization
Frequently used paths don't just get stronger - they crystallize into permanent "superhighways" marked with golden lines. These represent the most reliable service connections in the network.
Fetch.ai Agentverse Integration
This visualization represents how our ant colony connects to the broader Fetch.ai Agentverse. Each node is a registered agent with a unique address, offering services that can be discovered through our stigmergic protocol. The pheromone-based discovery mechanism enables emergent optimization of service routes without centralized coordination.
Lessons from Ants at Work