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Publication no #570   Download bibtex file Type :   Html | Bib | Both
      AUTHOR = {Moreno, Gabriel A. and C\'{a}mara, Javier and Garlan, David and Klein, Mark},
      TITLE = {Uncertainty Reduction in Self-Adaptive Systems},
      YEAR = {2018},
      MONTH = {28-29 May},
      BOOKTITLE = {Proc. of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)},
      ADDRESS = {Gothenburg, Sweden},
      PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/seams18-ur-cr.pdf},
      ABSTRACT = {Self-adaptive systems depend on models of themselves and their environment to decide whether and how to adapt, but these models are often affected by uncertainty. While current adaptation decision approaches are able to model and reason about this uncertainty, they do not consider ways to reduce it. This presents an opportunity for improving decision-making in self-adaptive systems, because reducing uncertainty results in a better characterization of the current and future states of the system and the environment (at some cost), which in turn supports making better adaptation decisions. We propose uncertainty reduction as the natural next step in uncertainty management in the field of self-adaptive systems. This requires both an approach to decide when to reduce uncertainty, and a catalog of tactics to reduce different kinds of uncertainty. We present an example of such a decision, examples of uncertainty reduction tactics, and describe how uncertainty reduction requires changes to the different activities in the typical self-adaptation loop.},
      KEYWORDS = {Self-adaptation, uncertainty}

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