Recursive Admissibility Corridors: Dynamic Tolerance Expansion and Convergence Under Weighted Cognitive Traversal

This paper introduces Recursive Admissibility Corridors as a structural framework for modelling recursive cognition as dynamically evolving admissibility geometry under weighted traversal pressure through time. The framework proposes that cognitive tolerance is not static, but progressively forms, expands, narrows, and converges through recursive engagement, symbolic weighting, environmental modulation, continuity inheritance, and approaching decision commitment. Unlike linear cognition models or static branching structures, the framework interprets cognition as a fluid recursive admissibility field in which possible pathways dynamically deform under convergence pressure. Future action states behave as recursive constraint attractors, progressively narrowing reversible traversal space until executable continuity crystallises into irreversible inheritance. The paper additionally introduces: • dynamic tolerance expansion, • recursive admissibility corridor formation, • convergence curvature, • recursive topology deformation, • continuity inheritance pressure, • distributed recursive traversal lattices, • and irreversible convergence boundaries. Figure 1 presents the foundational Recursive Admissibility Corridor Geometry illustrating: initiation-state fluidity, recursive expansion, weighted corridor deformation, and narrowing convergence toward action commitment. The framework remains intentionally structural rather than neurological. It does not propose new physical laws or clinical claims. Its purpose is recursive continuity modelling, admissibility interpretation, and geometric refinement within the Paton System cognitive branch.