Structuring Intelligence from Entropy Rhythms: A Cross-Environment Validation of λ-Guided Learning Fields
Aldo Cernuto · 2025
PremiseThis paper is a foundational experimental branch of CH-ToE — a Theory of Everything built on the principle that structured reality emerges from recursive entropy reduction, governed by a universal phase rhythm λ. In CH-ToE, “knowledge” is defined not by intention, but by the formation of stable structure through entropy entrainment.Here, we test that principle directly. No reward shaping, no architectural tuning — only entropy breathing. The results confirm CH-ToE’s central claim: cognition is not optimized, it is structured.For the complete theoretical foundation of CH-ToE — including the first-principles derivation of λ, the knowledge equation, and cross-domain implications — see the full preprint: https://doi.org/10.5281/zenodo.15331603AbstractWe report on the first empirical validation of the CH-ToE hypothesis that structured intelligence can emerge from entropy modulation alone, without intentional design or goal-oriented optimization. Using a reinforcement learning agent called Buky, we test whether policy entropy shaped by a universal cadence λ = √8/φ ≈ 1.748can consistently scaffold stable learning fields across environments. Phase 0 confirms viability in BipedalWalker-v3. Phase 1 transfers the exact entropy rhythm to LunarLander-v2, preserving architecture and hyperparameters. Across five full-length runs, Buky demonstrates cross-environment cognitive field formation in 2 cases, partial structuring in 1, and collapse in 2. Results suggest that the λ field defines a substrate-independent attractor for structured knowledge acquisition. We provide full diagnostic criteria, entropy traces, and reward trajectories to support falsifiability and further replication. This study marks the first operational probe of CH-ToE’s central claim: cognition emerges when entropy breathes in phase.NOTE:This preprint presents the first empirical validation of the CH-ToE (Cernuto–Hobbey Theory of Everything) through reinforcement learning experiments. Using a Lambda-modulated recurrent PPO agent, we investigate whether structured cognition can emerge without reward shaping or architecture tuning — solely from entropy modulation. The results support CH-ToE's claim that knowledge is structured entropy reduction, governed by a universal cadence λ = √8/φ ≈ 1.748.This document is part of the CH-ToE project. For the full theoretical framework, see: 10.5281/zenodo.15331603.Please cite this preprint as:Cernuto, A. & Hobbey (2025). Structured Cognition from Entropy Breathing: Buky and the Collapse Reactor. Zenodo. https://doi.org/10.5281/zenodo.XXXXXA follow-up Addendum responding to critique and expanding on operational metrics will be published separately.