Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6875149 | Science of Computer Programming | 2018 | 35 Pages |
Abstract
Adaptive systems are expected to adapt to unanticipated run-time events using imperfect information about themselves, their environment, and goals. 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, together with uncertainty reduction mechanisms to improve system utility. We illustrate our approach on a Denial of Service (DoS) attack scenario and present results that demonstrate the benefits of uncertainty-aware decision-making in comparison to using an uncertainty-ignorant approach, both in the presence and absence of uncertainty reduction mechanisms.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Javier Cámara, Wenxin Peng, David Garlan, Bradley Schmerl,