TITLE ISCIWI — Integrated Structural Computing / Intelligence Working Index: Core Architecture v1.2
Abstract
ISCIWI (Integrated Structural Computing / Intelligence Working Index) is a modular structural computing architecture derived from Structural System Theory (SST) and Structural Time Theory (STT). The system introduces a volumetric computing paradigm in which computational tasks evolve within a structural state space and converge toward stable configurations, replacing linear instruction execution with geometry-driven convergence. The architecture is organized around a single invariant kernel (Blocks A–O) and three deployment layers: Core Runtime, Analytical Extension, and AI Orchestration. All layers share one mathematical foundation. The kernel defines: a seven-component system state vector S(t) = (X, Y, Z, R, B, T, H_T) grounded in observable OS metrics; a structural stability potential Φ_s with five fully specified sub-indices (SCI, PFI, TPI, CPI, CSM); a distributed memory field μ(x,t) governed by a reaction-diffusion PDE derived from Network Memory Theory; a three-axis Prism controller Π_live(t) = (T(t), R(t)·B(t), D(t)) as the minimal deployable operational geometry; a softmax-normalized four-class regime forecast operator F_pred; a triadic strategic interaction model with operators U_i, ADR, DDR, HDR, TSBI, and SOS; and a stability-based structural security layer replacing signature matching with structural impact evaluation. The architecture is derived from the SST 12-theory corpus (DOI: 10.5281/zenodo.18967479) and implements its theoretical mechanics as an executable computing system. Deployment ranges from edge devices (Raspberry Pi class) to full analytical platforms. The complete mathematical kernel is publication-ready and implementation-ready.
Fields of Study & Subjects
Cognitive Computing and Networks
Complex Systems and Dynamics
Psychiatry
Mental Health
Neuroscience
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 March 2026
- Language
- EN