Abstract This monograph formalizes the Self-Referential Ignorance Cosmology (SRI-C) into a rigorous, mathematical, and falsifiable framework known as the Unified Theory of Self-Referential Ignorance (UT-SRI). We propose that the evolution of the universe is fundamentally driven by an informational constraint: no finite physical subsystem can completely represent or compute the totality of reality in which it is embedded, nor can it achieve infinite recursive depth in self-modeling due to strict energetic and physical boundaries (e.g., the Bekenstein bound). This persistent informational mismatch, termed Self-Referential Ignorance (SRI), acts as an epistemic and thermodynamic drive that generates adaptation, structural novelty, and complexification across all scales. We adopt the language of algorithmic information theory (Kolmogorov complexity) and conditional entropy to define evolutionary mechanics, propose a non-equilibrium complexity production equation, introduce empirically tractable proxy measures for I(R||M), and outline falsifiable predictions to distinguish UT-SRI from existing paradigms including Karl Friston's Free Energy Principle and standard statistical mechanics. A worked example grounding the core parabolic complexity curve in a concrete neural network setting is provided.
Angelito Enriquez Malicse (Fri,) studied this question.
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