Information Stability Theory: A Unified Ontology of Matter, Life, Mind, and Self

Classical physics, evolutionary biology, and cognitive science describe matter, life, and mind using separate conceptual foundations, despite the absence of any clear boundary in nature where one domain ends and another begins. Informa- tion Stability Theory (IST) proposes an ontological framework in which these do- mains correspond not to fundamentally different kinds of existence, but to differ- ent regimes of informational persistence. The theory models reality as the evolution of informational states under rule-governed dynamics, whereby stable patterns manifest as physical objects, self-preserving patterns as living systems, predictive patterns as minds, and recursively stabilized internal patterns as selves. A mathematical formulation is introduced in which patterns are defined as equivalence classes over the state space, and persistence is quantified by expected temporal sta- bility under system dynamics. Within this framework, life is characterized by the ability of informational patterns to act on their environment to increase their persistence, while cognitive processes are characterized by prediction-driven updates that improve persistence under uncertainty. IST is compatible with existing phys- ical theories when these are interpreted as describing different stability regimes: classical mechanics corresponds to high stability, relativity to stability under curvature, and quantum mechanics to low stability and rapid pattern change. The aim of IST is not to replace established scientific models, but to provide a shared ontological basis from which physical, biological, and cognitive phenomena can be interpreted within a single informational hierarchy.