Build Reasoning
Engines That Think
A framework for constructing domain-specific reasoning systems — from deductive logic chains to probabilistic inference graphs. Designed for engineers who need explainable, auditable AI decisions.
Forward and backward chaining over first-order logic. Unification, resolution, and Herbrand universe construction. Proof trees with full explanation traces.
Bayesian belief propagation over arbitrary graph structures. Variable elimination, belief revision, and uncertainty quantification built-in.
Arc-consistency and backtracking with conflict-directed backjumping. Define hard constraints as predicates; soft constraints as weighted penalties.
RDF/OWL ontology integration. SPARQL query interface. Incremental knowledge updates with consistency maintenance via truth maintenance system (TMS).
// Initialize a reasoning engine let engine = Reasoner::builder() .with_knowledge_base(ontology) .with_inference_rules(rules) .with_constraint_solver(csp) .build()?; // Run inference let result = engine .query("is_valid_path(A, B)") .explain(true) .timeout(Duration::from_millis(500)) .execute()?; // Inspect the proof trace for step in result.proof_trace() { println!("{}", step.render()); }