NESSField+SheathWorld: A Developmental Cognitive Architecture from Non-Equilibrium Statistical Physics

We present NESSField+SheathWorld, a developmental cognitive architecture grounded in non-equilibrium statistical physics. We establish a formal correspondence between PID control and the Fokker-Planck decomposition of non-equilibrium steady states (NESS), confirmed by independent derivation in the active inference literature. Single-particle experiments validate that FEP gradient descent produces cognitively meaningful behaviors (perception tracking, object permanence) while inevitably reaching thermal death; a multi-particle basin birth-death framework is proposed as theoretical resolution. The PID-FPE correspondence is numerically validated in 1D/2D; single-particle cognitive behaviors are experimentally confirmed; system-level emergence remains future work. This work was developed with AI-assisted literature review, mathematical proof verification, and LaTeX typesetting; all theoretical contributions, experimental design, and final decisions remain solely the author’s own. Keywords: Free Energy Principle, PID Control, Non-Equilibrium Steady State, Cognitive Architecture, Developmental Robotics

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-28
DOI
https://doi.org/10.5281/zenodo.21011453
Primary Topic
Reinforcement Learning in Robotics
Type
preprint
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NESSField+SheathWorld: A Developmental Cognitive Architecture from Non-Equilibrium Statistical Physics

Wei Liu
Zenodo (CERN European Organization for Nuclear Research)
Reinforcement Learning in Robotics
preprint

NESSField+SheathWorld: A Developmental Cognitive Architecture from Non-Equilibrium Statistical Physics

Wei Liu
preprint en

Abstract

We present NESSField+SheathWorld, a developmental cognitive architecture grounded in non-equilibrium statistical physics. We establish a formal correspondence between PID control and the Fokker-Planck decomposition of non-equilibrium steady states (NESS), confirmed by independent derivation in the active inference literature. Single-particle experiments validate that FEP gradient descent produces cognitively meaningful behaviors (perception tracking, object permanence) while inevitably reaching thermal death; a multi-particle basin birth-death framework is proposed as theoretical resolution. The PID-FPE correspondence is numerically validated in 1D/2D; single-particle cognitive behaviors are experimentally confirmed; system-level emergence remains future work. This work was developed with AI-assisted literature review, mathematical proof verification, and LaTeX typesetting; all theoretical contributions, experimental design, and final decisions remain solely the author’s own. Keywords: Free Energy Principle, PID Control, Non-Equilibrium Steady State, Cognitive Architecture, Developmental Robotics

Zenodo (CERN European Organization for Nuclear Research)
Oldham Council (GB)
Reinforcement Learning in Robotics
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