Towards Self-Explainable Cyber-Physical Systems
August 13, 2019 Β· Declared Dead Β· π 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)
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Authors
Mathias Blumreiter, Joel Greenyer, Francisco Javier Chiyah Garcia, Verena KlΓΆs, Maike Schwammberger, Christoph Sommer, Andreas Vogelsang, Andreas Wortmann
arXiv ID
1908.04698
Category
cs.AI: Artificial Intelligence
Citations
43
Venue
2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)
Last Checked
4 months ago
Abstract
With the increasing complexity of CPSs, their behavior and decisions become increasingly difficult to understand and comprehend for users and other stakeholders. Our vision is to build self-explainable systems that can, at run-time, answer questions about the system's past, current, and future behavior. As hitherto no design methodology or reference framework exists for building such systems, we propose the MAB-EX framework for building self-explainable systems that leverage requirements- and explainability models at run-time. The basic idea of MAB-EX is to first Monitor and Analyze a certain behavior of a system, then Build an explanation from explanation models and convey this EXplanation in a suitable way to a stakeholder. We also take into account that new explanations can be learned, by updating the explanation models, should new and yet un-explainable behavior be detected by the system.
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