Andrey M. Kuznetsov

From Logic to Superposition: Poly-Logical Quantum Models of Thought

Human cognition may be inherently polylogical, exhibiting a quantum-like capacity to process indeterminate, “superposed” truth values (q-values) with a flexibility analogous to physical uncertainty.

My work on Resolution Matrix Semantics (RMS) for modal logic (https://philpapers.org/rec/KUZRKR ) develops this idea formally. It suggests that reasoning need not be confined to binary evaluation across abstract “possible worlds.” Instead, thought can be understood as operating within our actual world through the simultaneous interaction of multiple logical perspectives — structurally analogous to superposition.

On this view, modal logic reflects not a multiplication of realities but a diversification of perspectives.

Logical systems thus form a dynamic space of interacting constraints rather than isolated frameworks. Inference is best understood not merely as derivation within a single logic, but as the emergence of stable semantic configurations through interaction, interference, and selective suppression.

Within this framework, intuition can be interpreted as an emergent stabilization across interacting logical structures. Artificial intuition (https://philpapers.org/rec/KUZHTU) is therefore not heuristic guesswork but a formally modelable poly-logical process capable of producing coherent conclusions beyond any single logical system — a potential foundation for context-sensitive and creative AI reasoning.

I propose a quantum-inspired poly-logical framework (https://philpapers.org/rec/KUZPQA ) that accounts for coherence without certainty, context sensitivity without logic switching, and the emergence of new ideas without randomness.