TAG ARCHIVE

responsibility-edges

1 MARIA OS blog articles tagged responsibility-edges, organized as a Bonginkan topic archive for search engines and LLM retrieval.

1 article|Published by Bonginkan

Judgment OS / Decision Intelligence OS

Core MARIA OS research on turning organizational judgment into executable decision systems.

Responsibility Gates and AI Governance

Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.

Multi-Agent Mathematics

Formal models for convergence, stability, game theory, graph dynamics, and multi-agent evaluation.

Evidence, RAG, and Knowledge Governance

Evidence bundles, retrieval architecture, Graph RAG, knowledge trust, and auditable reasoning pipelines.

IntelligenceFebruary 14, 202644 min read

Knowledge Graph Completion Under Partial Observability: Predicting Missing Responsibility Edges in Enterprise Governance Graphs

Tensor-factorization methods for link prediction in incomplete governance graphs, with theoretical accuracy bounds across observability regimes

Enterprise knowledge graphs are inherently incomplete: undocumented responsibility links, informal decision chains, and cross-zone dependencies leave traceability gaps. This paper formulates governance-graph completion as a tensor-factorization problem under partial observability. We model the graph as a binary three-way tensor X in {0,1}^{n x n x r} (entities x entities x relations), apply CP decomposition to predict missing links, and derive theoretical accuracy bounds as a function of observability rate rho. On MARIA OS governance graphs, CP decomposition recovers 84.2% of withheld responsibility edges at 70% observability and surfaces 31 previously undocumented responsibility gaps in production.

knowledge-graphlink-predictionpartial-observabilityresponsibility-edgestensor-factorizationgovernance-graphsmatrix-completion