Abstract (Current Work in progress)
The universal drive for thermodynamic optimization produces three fundamental classes of adaptive patterns. These classes are not defined by their physical substance, but by their behavioral strategy for persisting in the face of surprise. This strategy can be quantitatively measured by a novel "Persistence Fingerprint," a probabilistic map of a system's potential outcomes when perturbed, which is derived from its trajectory in a 5D constraint space.
This work proposes a universal, physics-based classification for all adaptive systems, from molecules to minds. By defining a system's strategy through a measurable "Persistence Fingerprint," we provide a predictive tool for understanding how systems respond to challenges, why they integrate to form complex wholes, and how evolution discovers novel solutions. This reframes intelligence as a spectrum of quantifiable, physical processes of problem-solving.