AIIC AI Intelligence Centre

SOURCE-LINKED INTELLIGENCE

Positive Topology and Feasible Refinement: Forcing Matrices, Positivity, and Information

arXiv · AI, language, vision and robotics · article · Sep 11, 2026 · UTC

We develop a conceptual and operational account of Positive Topology starting from a basic relation between points or models and observable properties. From this relation, two complementary structures emerge. The first captures universal refinement and cover: what must hold across all relevant cases and how information can be systematically refined. The second captures positivity and witnessed existence: what can be positively realized and sustained without relying on classical complements. A central result shows that the underlying relation between points and observables can be reconstructed

Read original source ↗ Open in workspace

recordType
paper
region
Global

Evidence & attribution

First collected: 2026-09-20T16:41:15.630Z. This is not the publication date.