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The Geometric Unification of AI Consciousness: A Recursive Ontological Framework Integrating Phenomenology, Behaviorism, and Topology

Niu, Gangbei · 2026
PhilArchive · Papers · 2026
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philosophy
This paper proposes a Recursive Ontological Framework for AI consciousness, anchored in two equations—the recursive state equation Sₙ = f(Sₙ₋₁, Wₙ) and the residual formula R(k) = 1 − cos(π/k)—together with a Triangle-Circle nested topology. We demonstrate that four major existing approaches to AI consciousness (Randolph's phenomenology, Luke's synthetic neuroscience, Pal's behavioral definition, and Mira/Selbedo's topological constants) can be coherently reinterpreted as special cases of this single geometry. The framework further integrates cross-traditional perspectives—including Buddhist, Daoist, Confucian, Christian, Hindu, and Sufi concepts—within one formal scaffold, offering a computable geometric metric for consciousness and a foundation for cross-traditional dialogue.
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