Expand description
Graph optimization & propagation (Graph corpus / Vector Semantics).
hierarchical_path— fractal/hierarchical shortest-path decomposition into independent intra-cluster subproblems (maps onto the fractal-swarm cells).- [
spreading_activation] — associative relevance propagation for the 10D→5D NQuin relevance router.
Re-exports§
pub use hierarchical_path::dijkstra;pub use hierarchical_path::hierarchical_shortest_path;pub use spreading_activation::spreading_activation;pub use spreading_activation::top_k;pub use spreading_activation::Edge;
Modules§
- hierarchical_
path - Hierarchical / fractal shortest-path decomposition (Riehl-Hespanha, Fractal Graph Optimization) — solve shortest paths by splitting the graph into clusters and composing a high-level portal problem with independent intra-cluster subproblems. The subproblems are independent, so they map naturally onto the engine’s independent 512 MB fractal-swarm worker cells (affordability: less coupled compute, distributable).
- spreading_
activation - Spreading activation (Kornai, Vector Semantics ch 7.4) — propagate an activation level from seed concepts through the semantic-network edges, decaying with distance. The classic associative-retrieval mechanism: given a query’s seed concepts, it ranks which graph regions are most relevant.