Hallucination Suppression in a Persistent Cognitive Machine via Geometric Epistemic Conditioning and Symplectic Knowledge Protection

A computer system comprising at least one processor, a memory, and a plurality of programming instructions stored on a non-transitory memory and configured to cause the at least one processor to:

• maintain an epistemically conditioned manifold equipped with a semantic metric measuring distances between cognitive configurations, an almost-complex structure providing a rotational operator on the tangent space of the manifold, a symplectic form satisfying almost-Kähler compatibility with the semantic metric and the almost-complex structure, and an epistemic connection defined on a line bundle over the manifold and geometrically independent of the semantic metric, wherein a curvature of the epistemic connection measures local epistemic strain and a holonomy of the epistemic connection around a closed reasoning loop measures path-level evidential coherence;
• process incoming data through an extended projection operator that maps the incoming data onto the epistemically conditioned manifold through a pipeline comprising semantic attachment that locates the incoming data on the manifold, structural compatibility checking that verifies consistency with local geometric structure, symplectic admission control that prevents compression of consolidated knowledge below an irreducible symplectic volume, and epistemic evaluation that assesses evidential coherence using the epistemic connection, producing for each datum an outcome classification selected from among absorb, defect, veto, and flag;
• implement a multi-layer hallucination resistance architecture comprising a topological detection layer that identifies reasoning trajectories lacking structural support in the manifold, an epistemic phase monitoring layer that detects divergence between the epistemic connection and the semantic metric, and a symplectic capacity protection layer that prevents displacement of consolidated knowledge by incoming data of insufficient symplectic volume;
• and
• distinguish justified from unjustified cognitive content that is metrically indistinguishable under the semantic metric by evaluating the holonomy of the epistemic connection, wherein justified content exhibits coherent epistemic phase accumulation around closed reasoning loops and unjustified content exhibits incoherent or divergent epistemic phase accumulation.