@InProceedings{2017:Uncertainty:Camara,
      AUTHOR = {C\'{a}mara, Javier and Peng, Wenxin and Garlan, David and Schmerl, Bradley},
      TITLE = {Reasoning about Sensing Uncertainty in Decision-Making for Self-Adaptation},
      YEAR = {2017},
      MONTH = {5 September},
      BOOKTITLE = {Proceedings of the 15th International Workshop on Foundations of Coordination Languages and Self-Adaptive Systems (FOCLASA 2017)},
      VOLUME = {10729},
      SERIES = {Lecture Notes in Computer Science},
      PUBLISHER = {Springer},
      PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/CPGS-CR-foclasa17.pdf},
      ABSTRACT = {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 paper contributes a formal analysis technique that explicitly considers uncertainty in sensing when reasoning about the best way to adapt. We illustrate our approach on a Denial of Service (DoS) attack scenario and present some preliminary results that show the benefits of uncertainty-aware decision-making with respect to using an uncertainty-ignorant approach.},
      KEYWORDS = {Self-adaptation, uncertainty}
}