From Affordances to Freedom Intelligence: Adaptive PathSpace, Conditional Commitment, and the PLANTA Tree Method

Abstract

Ecological approaches explain perception through meaningful relations between an organism and its environment. A complementary computational problem concerns the resolution at which such relations must be differentiated before action can proceed. This paper develops that problem within the Architecture of Freedom Intelligence (AFI) and its proposed PLANTA Perception Method. A PLANTA Tree is formalized as a revisable representation of perceived continuations, organized into functional clusters and selectively refined when a distinction can change the next action. The account separates physical availability from perceived availability, uncertainty about represented alternatives from unrepresented Opacity, and commitment to a first action from commitment to a complete future. A conditional common-prefix result specifies when unresolved trajectories support the same executable next step; a bounded-cost corollary gives one implementation without making scalar optimization a universal definition of perception. Five constructed cases—commuting, food shopping, career preparation, moving furniture, and robotic-material reconfiguration—show the actual trees, their assumptions, and the counterfactuals that would reverse their conclusions. The resulting framework supports falsifiable tests of whether adaptive representation improves the allocation of perceptual and computational effort.