TAG ARCHIVE
conflict-detection
2 MARIA OS blog articles tagged conflict-detection, organized as a Bonginkan topic archive for search engines and LLM retrieval.
Agentic Company Architecture
Research on human-agent organizations, delegation boundaries, role topology, and governed autonomy.
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.
Linear Algebra Model for Negative Correlation Detection Across Business Universes
Using eigendecomposition of correlation matrices to identify conflicting objectives across business universes
When business universes optimize in opposing directions, organizations incur both direct conflict cost and wasted optimization effort. This paper develops a linear-algebra framework for detecting negative correlations using correlation matrices, eigendecomposition, and spectral analysis. Negative eigenvalues in inter-universe correlation structures identify conflict clusters that require governance intervention rather than additional local optimization.
Spectral Decomposition of Conflict Clusters: Extracting Opposition Factions via Laplacian Eigenvectors
Using graph Laplacian analysis and Fiedler vectors to reveal hidden factional structure in multi-agent conflict networks
Repeated agent conflicts can form factional structures that are hard to detect from pairwise analysis alone. This paper applies spectral graph theory by constructing conflict-graph Laplacians, analyzing eigenspectra, and using the Fiedler vector to partition opposition groups. We extend to k-faction decomposition via higher eigenvectors and present visualization methods that translate spectral patterns into operational governance signals.