CMU-ISR-17-110 Institute for Software Research School of Computer Science, Carnegie Mellon University
Uncertainty in Self-Adaptive Systems
Javier Cámara, David Garlan, Won Gu Kang, July 2017
Self-Adaptive systems are expected to adapt to unanticipated run-time events using imperfect information about their environment. This entails handling the effects of uncertainties in decision-making, which are not always considered as a first-class concern. This technical report summarizes a set of existing techniques and insights into addressing uncertainty in self-adaptive systems and outlines a future research agenda on uncertainty management in self-adaptive systems. The material in this report is strongly informed by our own research in the area, and is therefore not necessarily representative of other works.
45 pages
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