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.

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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

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Cyber
  • Engineered Resilient Systems
  • Sensors

DTIC Thesaurus Topics

  • Adaptive Systems
  • Artificial Intelligence
  • Computer Science
  • Control Systems
  • Engineering
  • Fuzzy Sets
  • Game Theory
  • Information Retrieval
  • Machine Learning
  • Normal Distribution
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Reliability
  • Software Development
  • Systems Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Systems Analysis and Design