ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
121 articles · Published by MARIA OS
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.
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.
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Complete list of all 121 published articles. EN / JA bilingual index.
121 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
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