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Ontological Conflict Theory for Computational Complexity

Authors: Ednyashev, Sanal;

Ontological Conflict Theory for Computational Complexity

Abstract

**Meta-Structural Universality of Ontological Conflict Theory (OCT)** This work presents the Ontological Conflict Theory (OCT) as a unifying, meta-theoretical framework for computational complexity. Unlike specialized approaches, OCT establishes formal isomorphism across different domains of computational theory via a single measure of structural conflict: μ(S, Q). The key insight of OCT is that computational hardness arises not merely from input size or syntactic structure, but from an inherent mismatch between the internal structure (S) of a problem and its external constraints (Q). OCT derives computational properties directly from the structural characteristics of a problem, without reliance on assumptions about the underlying computational model. This enables the formal derivation of equivalences between phenomena across deterministic, nondeterministic, quantum, analog, and self-referential systems. Because of its mathematically rigorous foundation, OCT serves not as a philosophical narrative but as a precise tool for structural comparison and classification of computational problems. The conflict measure μ becomes a unifying metalanguage for analyzing the intrinsic complexity of tasks across paradigms, enabling formal translation of results between models without loss of rigor. This meta-structural capacity positions OCT as a new layer in the theory of computation — not as a replacement of classical complexity theory, but as its structural generalization, with potential implications in logic, algorithm design, and the foundations of mathematics.

Keywords

Kolmogorov measure, structural complexity, unexplainability, meta-structural analysis, SB-barrier, μ(S,Q), fixed-point logic, descriptive complexity, oct, Δμ, logical indistinguishability, Ednyashev, Ontological Conflict Theory, inexpressibility, P vs NP

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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