The Universal Perception: A Falsification Programme for Recursive PathSpace Resolution Across Matter, Life and Machines

Abstract

Perception is ordinarily studied in organisms and artificial agents, whereas physical propagation is described through dynamics, constraints and quantum amplitudes. The Architecture of Freedom Intelligence proposes a broader hypothesis: systems follow the lightest path according to their Perception. We examine whether this statement can become a falsifiable cross-domain model rather than a retrospective description. We represent Perception as an adaptive sequence of path spaces and relative distortion fields, with context-dependent quotient partitions supporting generalization and particularization. A conditional Robust Follow theorem identifies when all potentially optimal trajectories share the same next action, permitting action before distant futures are resolved. We show that positive multiplicative distortion is an exponential reparameterization of additive cost, that normalization to one adds no predictive content, and that a common positive exponent cannot change path rankings. In 400 deterministic synthetic worlds, a reference action certificate selects an optimal first action in every case and saves a mean 1.27 observations relative to full-path certification.