Nature Based Functional Analysis, 'general intelligence' and causality in science

NeurIPS 2025 Workshop CauScien Submission35 Authors

Keywords: entropy, signal entropy, information theory, semantic, dialectic, theory of meaning, natural selection, general intelligence, super intelligence, functional analysis, dual aspect theory

TL;DR: A 'scientific' Nature-based foundation for general and super intelligence modeling.

Abstract: This paper names structural fundaments for general intelligence and for mapping causality in science. Three scientific models are used to pose an empiric core, beyond artificial intelligence's statistics. The models are Boltzmann's thermodynamic entropy, Shannon's signal entropy, and Darwinian natural selection, joined to frame all of science-and-engineering with general terms. The paper thus names 'principles' and 'primitives' for intelligence and intelligence building, along with a dualist-triune (2-3) fractal pattern. It claims a purely structural account of the cosmos is possible, prior to adding other 'detail', as a multi-level Entropic/informatic continuum with 'functional degrees of freedom'---all as a mildly-modified view of signal entropy's structural aspects.

Submission Number: 35