exo-hypergraph

Hypergraph substrate for higher-order relational reasoning in the EXO-AI cognitive substrate.

Features

Hyperedge Support: Relations spanning multiple entities (not just pairwise)
Topological Data Analysis: Persistent homology and Betti number computation (interface ready, full algorithms to be implemented)
Sheaf Theory: Consistency checks for distributed data structures
Thread-Safe: Lock-free concurrent access using DashMap

Architecture

This crate implements the hypergraph layer as described in the EXO-AI architecture:

HypergraphSubstrate
├── HyperedgeIndex        # Efficient indexing for hyperedge queries
├── SimplicialComplex     # TDA structures and Betti numbers
└── SheafStructure        # Sheaf-theoretic consistency checking

Usage

use exo_hypergraph::{HypergraphSubstrate, HypergraphConfig};
use exo_core::{EntityId, Relation, RelationType};

// Create hypergraph
let config = HypergraphConfig::default();
let mut hypergraph = HypergraphSubstrate::new(config);

// Add entities
let e1 = EntityId::new();
let e2 = EntityId::new();
let e3 = EntityId::new();

hypergraph.add_entity(e1, serde_json::json!({"name": "Alice"}));
hypergraph.add_entity(e2, serde_json::json!({"name": "Bob"}));
hypergraph.add_entity(e3, serde_json::json!({"name": "Charlie"}));

// Create 3-way hyperedge (beyond pairwise!)
let relation = Relation {
    relation_type: RelationType::new("collaboration"),
    properties: serde_json::json!({"project": "EXO-AI"}),
};

let hyperedge_id = hypergraph.create_hyperedge(
    &[e1, e2, e3],
    &relation
).unwrap();

// Query topology
let betti = hypergraph.betti_numbers(2);  // Get Betti numbers β₀, β₁, β₂
println!("Topological structure: {:?}", betti);

Topological Queries

Betti Numbers

Betti numbers are topological invariants that describe the structure:

β₀: Number of connected components
β₁: Number of 1-dimensional holes (loops)
β₂: Number of 2-dimensional holes (voids)

let betti = hypergraph.betti_numbers(2);
// β₀ = connected components
// β₁ = loops (currently returns 0 - stub)
// β₂ = voids (currently returns 0 - stub)

Persistent Homology (Interface Ready)

The persistent homology interface is implemented, with full algorithm to be added:

use exo_core::TopologicalQuery;

let query = TopologicalQuery::PersistentHomology {
    dimension: 1,
    epsilon_range: (0.0, 1.0),
};

let result = hypergraph.query(&query).unwrap();
// Returns persistence diagram (currently empty - stub)

Implementation Status

✅ Complete:

Hyperedge creation and indexing
Entity-to-hyperedge queries
Simplicial complex construction
Betti number computation (β₀)
Sheaf consistency checking
Thread-safe concurrent access

🚧 Stub Interfaces (Complex algorithms, interfaces ready):

Persistent homology computation (requires boundary matrix reduction)
Higher Betti numbers (β₁, β₂, ...) require Smith normal form
Filtration building for persistence

Dependencies

exo-core: Core types and traits
petgraph: Graph algorithms
dashmap: Concurrent hash maps
serde: Serialization

License

MIT OR Apache-2.0

exo-hypergraph 0.1.0