A systems theoretic perspective on open architectures for learning systems

Tyler Cody; Peter A Beling

doi:10.1117/12.3012391

6 June 2024 A systems theoretic perspective on open architectures for learning systems

Tyler Cody, Peter A Beling

Proceedings Volume 13058, Disruptive Technologies in Information Sciences VIII; 1305808 (2024) https://doi.org/10.1117/12.3012391
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

The advancement of open architecture ecosystems is fundamentally dependent on the interoperability, scalability, and adaptability of their constituent elements. As Machine Learning (ML) systems become increasingly integral to these ecosystems, the need for a systematic approach to engineer, deploy, and re-engineer them grows. This paper presents a novel modeling approach based on recently published, formal, systems-theoretic models of learning systems. These models serve dual purposes: first, they give a theoretical grounding to standards that govern the architecture, functionality, and performance criteria for ML systems; second, they allow for requirements to be specified at various levels of abstraction to ensure the systems are intrinsically aligned with the overall objectives of the open architecture ecosystem they belong to. Through the proposed modeling approach, we demonstrate how the adoption of standardized models can significantly enhance interoperability between disparate machine learning systems and other architectural components. Further, we relate our framework to on-going efforts such as Open Neural Network Exchange (ONNX). We identify how our approach can be used to address limitations in government acquisition processes for ML systems. The proposed systems-theoretic framework provides a structured methodology that contributes to the foundational building blocks for open architecture ecosystems for ML systems, thereby advancing the state-of-the-art in complex system integration.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tyler Cody and Peter A Beling "A systems theoretic perspective on open architectures for learning systems", Proc. SPIE 13058, Disruptive Technologies in Information Sciences VIII, 1305808 (6 June 2024); https://doi.org/10.1117/12.3012391

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