Modeling a Reference Architecture for Concept Drift Adaptation Systems

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Presented at HICSS 2025 by

Martin Trat

Matthes Elstermann

Jana Deckers

Jivka Ovtcharova

The democratization of artificial intelligence (AI) technology is rapidly progressing and becoming an integral functional part of systems in diverse domains. To maximize the utility of AI in such contexts, ensuring its robustness is of critical significance. The research field of concept drift adaptation (CDA) focuses on the development of strategies aimed at sustaining AI robustness. Despite their availability, such strategies remain under-utilized for AI system design in practice. It is therefore crucial to enable AI system designers of various backgrounds to implement CDA systems as well as understand their operational intricacies easily. This work analyzes the use of the formal modeling paradigm Subject Orientation as a means to describe CDA systems in a strictly consistent manner that avoids ambiguities and leverages this paradigm to design and propose a reference architecture for such systems.