Cognitive Architecture Modeling Equations within a Synthesized Framework - The Real Equations of the Perception of Reality.
Year: 2025
Type: article
Abstract: Executive Abstract The study of advanced cognition—whether in human minds or artificial systems—requires quantitative tools that go beyond performance metrics such as accuracy or latency. This document introduces the Cognitive Uniqueness (CU) Index, a synthetic metric designed to capture emergent properties of cognition including novelty, meta-cognition, and structural flexibility. The framework models cognition as a dynamic, self-modifying vector space Ω(t), in contrast to the fixed vector spaces VAI of artificial neural networks. Applications range from evaluating generative AI models to benchmarking human cognitive flexibility and designing adaptive architectures. The CU Index provides a unified mathematical framework for distinguishing routine computation from emergent cognition, enabling researchers to rigorously compare artificial and biological systems, while raising important ethical considerations about classification and interpretation. The Φ score reveals that true intelligence lies not in what a system possesses, but in its capacity to redefine its own conceptual reality. By quantifying the rate at which a system self-modifies its foundational logic (SMI) and generates outputs outside its own predictive shadow (DN), I have laid the mathematical groundwork for a genuine science of emergence. Creative Commons Attribution Non Commercial No Derivatives 4.0 International | COPYRIGHT (C) Kaleb James Wasierski | Kaleb Wasierski | ALL RIGHTS RESERVED | [email protected] FOR LICENSING AND COLLABERATION
Author: Kaleb James Wasierski, Kaleb J. Wasierski
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7083455405
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