Reversible Navigation in Dynamic Cognitive Manifolds

Abstract

Systems and methods are disclosed for reversible navigation of cognitive state in artificial intelligence systems that operate continuously under finite representational capacity. The methodology represents internal cognition as navigation on a continuous, differentiable cognitive manifold wherein reasoning inference and decision-making correspond to traversals along admissible trajectories. Reversibility is achieved through holonomy-indexed semantic transport which preserves path-dependent effects in a compressed and structurally invariant form without replay or explicit storage of execution history. The methodology involves maintaining a composite cognitive state including a manifold location an active holonomy set an interface configuration and a residual state. In an embodiment, a navigation engine executes forward and reverse traversal operations; a transport journal manager maintains bounded procedural context required for executable reversibility by creating journal entries; an admissibility checker verifies that operations satisfy structural constraints; and control logic coordinates conditional reversibility in cases of resource constraints.

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