GISMOL: A General Intelligent Systems Modelling Language

Manuscript submitted February 9, 2026; accepted March 12, 2026; published May 20, 2026

Abstract—This paper presents General Intelligent System Modeling Language (GISMOL), a prototype Python-based framework implementing Constrained Object Hierarchies (COH)—a neuroscience-inspired theoretical framework for Artificial General Intelligence (AGI). GISMOL is currently under active development as a research prototype and has not yet been deployed in production environments at scale. COH and GISMOL together provide a unified language for modelling and implementing intelligent systems across diverse domains including healthcare, manufacturing, finance, and governance. The framework bridges symbolic AI and neural computation through its core architecture of constraint-aware objects with embedded neural components, hierarchical reasoning capabilities, and natural language integration. We demonstrate how GISMOL translates COH’s formal 9-tuple representation into executable systems with six comprehensive case studies, showing its versatility in modelling complex intelligent behaviors while maintaining theoretical rigor. The implementation includes specialized modules for neural integration, multi-domain reasoning, and natural language processing, all built around the COHObject abstraction that encapsulates intelligence as constrained hierarchical structures.

keywords—artificial general intelligence, constrained object hierarchies, neuro-symbolic AI, intelligent systems modelling, constraint programming, hierarchical reasoning, Python framework, constraint reasoning

Cite: Harris Wang,"GISMOL: A General Intelligent Systems Modelling Language," Journal of Advances in Artificial Intelligence, vol. 4, no. 2, pp. 104-124, 2026. doi: 10.18178/JAAI.2026.4.2.104-124

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).