memgraph-aco-queries

Query pheromone graphs in Memgraph by retrieving candidate nodes ranked by pheromone strength and fitness using Cypher queries. Connect via gqlalchemy, inspect TRAIL edges with pheromone deposits, and extract top candidates to surface leading factor prospects for your ACO workflow.

Ant Colony Optimization is a swarm intelligence algorithm where artificial ants deposit pheromones on promising paths. In prime factorization, ACO explores candidate factors by reinforcing high-fitness paths through pheromone trails, enabling collaborative convergence toward factoring RSA-style moduli.

Yes. Memgraph stores PrimeCandidate nodes, TRAIL edges with pheromone and timestamp data, and fitness metrics. Query convergence metrics, track hot candidates across iterative runs, and validate candidate paths against your target modulus using graph analytics.

Install gqlalchemy and connect to Memgraph locally or remotely at the standard port using `mg = Memgraph(host="localhost", port=7687)`. Load prime candidates into the graph, then run Cypher queries to inspect pheromone trails and extract leading factor candidates.

Pheromone deposition strengthens TRAIL edges when ants find fit candidates, while evaporation reduces older deposits over time. This dual mechanism guides the swarm toward high-quality factors while preventing stagnation on suboptimal paths.

This Skill targets educational demonstrations of swarm intelligence applied to factoring. For production cryptanalysis, consult domain-specific tools and security best practices; ACO is suited for learning, not replacing established factorization algorithms at scale.