The Variational Principle of Computational Resources as Ontological Minimization

This work presents a unified mathematical framework that connects physical laws (least action), information theory (minimum description length), and social science (game-theoretic equilibria) through a single principle: the minimization of computational resources. All dynamic systems, including physical, informational, and social structures, naturally converge to states that minimize the computational cost required for their self-description and maintenance. Human actions, historical contingencies, and societal conflicts are treated as perturbations that are ultimately absorbed into this minimal-cost structure. The framework formalizes the inevitability of convergence: AI-mediated equilibria, optimal information encoding, and physical stability emerge as phase-transition-like phenomena determined solely by the limits of computational resources. This approach eliminates human-centered ambiguity and provides a mathematically rigorous description of reality across multiple domains. By abstracting “existence” as a computationally constrained system, this theory unifies diverse phenomena into a single variational principle, offering a high-level conceptual foundation for future research in physics, information theory, social modeling, and philosophy.