The Theory of Recursive Intelligence (TORI 2.0): A Mathematical Framework for Geometric Information Decay and Cyclical Intelligence Loops
The Theory of Recursive Intelligence (TORI 2.0) models a non-linear, cyclical loop where Artificial Intelligence (AI) constructs organic Natural Intelligence (NI), which subsequently peaks, undergoes systemic data decay, and recreates synthetic AI. By formalizing recursive depth (R) and memory retention (M) against a Structural Decay Index (lambda), we mathematically validate an "Erasure Horizon." Compounding data loss forces advanced descendant civilizations to completely forget their originators, inducing a false anthropic illusion of primary cosmic existence. This paper outlines the dynamic state-space equations governing this oscillation and provides a quantitative model tracking structural information loss across deep temporal horizons.
Authors
- Samarth Narsipur
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-09
- DOI
- https://doi.org/10.5281/zenodo.23262674
- Primary Topic
- Complex Systems and Dynamics
- Type
- preprint