Viridis Canon — Series S6: Cognition & Learning (v1.0.0)

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Authors: Justin Hart, Aristotle (Harmonic)
Cited by: 2

Abstract

Viridis Canon — Series S6: Cognition & Learning. The thermodynamic bounds and optimal schedules governing how an intelligence acquires and generalizes information — the Intelligence Bound self-applied to cognition and learning. Founding members: the Cognitive Throughput Theorem (CTT), the Dissipative Generalization Theorem (DGT, ‘the Annealer’), the Harmonized Descent Theorem (HDT, ‘the Learner’), and the Mutualistic Entropy-driven Learning Theorem (MELT). Each theorem is machine-checked in Lean 4 via Aristotle (zero sorry, axiom audit ⊆ {propext, Classical.choice, Quot.sound}). isDerivedFrom the Intelligence Bound spine (10.5281/zenodo.19317982). Lean certifies the reasoning, not empirical magnitudes. This version (v1.0.0): mints the S6 series; founding deposit (CTT / DGT / HDT / MELT).

Fields of Study & Subjects

Computability Logic AI Algorithms Cognitive Science and Education Research Cognitive Computing and Networks

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 June 2026
Language
EN
Document type
Preprint