Minimizing Execution Duration in the Presence of Learning-Enabled Components

  • Kunal Agrawal
  • , Alan Burns
  • , Abhishek Singh
  • , Sanjoy Baruah

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Autonomous systems are increasingly using components that incorporate machine learning and other AI-based techniques in order to achieve improved performance. We address the problem of assuring correctness in safety-critical systems that use such components. We investigate an approach which formulates the problem as one in which performance is an objective function to be optimized while safety is a hard constraint that must be satisfied. We then apply heuristics and algorithmic techniques from optimization theory in order to solve the resulting constrained optimization problem.

Original languageEnglish
Title of host publicationProceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
EditorsGiorgio Di Natale, Cristiana Bolchini, Elena-Ioana Vatajelu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1644-1649
Number of pages6
ISBN (Electronic)9783981926347
DOIs
StatePublished - Mar 2020
Event2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020 - Grenoble, France
Duration: Mar 9 2020Mar 13 2020

Publication series

NameProceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020

Conference

Conference2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
Country/TerritoryFrance
CityGrenoble
Period03/9/2003/13/20

Keywords

  • Learning-enabled components (LECs)
  • Performance optimization
  • Run-time monitoring
  • Safetycritical systems
  • Typical analysis

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