Researchers at the University of Victoria in Canada recently conducted a study and pre-published the results as a paper on arXiv. The paper provides a framework for classifying safety-critical self-adaptive systems and differentiating them from other robotic solutions. The objective of the work was to formalize the idea of safety-critical self-adaptive systems and help roboticists understand the systems better.
The researchers devised a new taxonomy for classifying different adaptations performed by self-adaptive systems. The taxonomy focuses on the safety or hazards associated with various adaptations. The overarching intent is to delineate the meaning of safe adaptation and the features that distinguish it from any other form of adaptation.
This research work could guide studies focusing on developing self-adaptive systems operating in safety-critical conditions. Ultimately, others could use this work to understand the potential of these systems for different real-world implementations.
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