Uncertainty in Self-Adaptive Systems: Categories, Management, and Perspectives
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 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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2017
- Accession Number
- AD1086752
Entities
People
- Bradley Schmerl
- David Garlan
- Javier Cámara
- Wenxin Peng
- Won G. Kang
Organizations
- Carnegie Mellon University