Fuzzy Representation for Flexible Requirement Satisfaction

Ratih N.E. Anggraini*, T. P. Martin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)
261 Downloads (Pure)

Abstract

The need for adaptive systems is growing with the increasing number of autonomous entities such as software systems and robots. A key characteristic of adaptive systems is that their environment changes, possibly in ways that were not envisaged at design-time. These changes in requirements, model and context mean the functional behaviour of a system cannot be fully defined in many cases, and consequently formal verification of the system is not possible. In this research, we propose a fuzzy representation to describe the result of requirement verification. We use an adaptive assisted living system as the case study. The RELAX language is used to create a flexible system specification. We model and simulate the system using UPPAAL 4 and use a fuzzy approach to translate the simulation result into fuzzy requirement satisfaction. The result shows the benefit of a more flexible representation by describing the degree of requirement satisfaction rather than a strict yes/no Boolean judgment.

Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems -
Subtitle of host publicationContributions Presented at the 17th UK Workshop on Computational Intelligence
EditorsFei Chao , Steven Schockaert , Qingfu Zhang
PublisherSpringer
Pages28-36
Number of pages9
ISBN (Electronic)9783319669397
ISBN (Print)9783319669380
DOIs
Publication statusPublished - 5 Sep 2017
Event17th UK Workshop on Computational Intelligence, UKCI 2017 - Cardiff, United Kingdom
Duration: 6 Sep 20178 Sep 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume650
ISSN (Print)2194-5357

Conference

Conference17th UK Workshop on Computational Intelligence, UKCI 2017
CountryUnited Kingdom
CityCardiff
Period6/09/178/09/17

Keywords

  • Adaptive system
  • Fuzzy
  • Requirement satisfaction

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