Research Challenges for Combined Autonomy, AI, and Real-Time Assurance

Tarek Abdelzaher, Sanjoy Baruah, Chris Gill, Eugene Vorobeychik, Ning Zhang, Xuan Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Advances in machine intelligence revolutionized a broad category of safety-critical and mission-critical applications, but important challenges remain when applying these solutions at the embedded network edge, as opposed to resource-rich contexts. What challenges stem from deploying cost-sensitive applications on lower-end devices to offer AI at the point of need? We present an overview of key research challenges that must be addressed to provide assurance of timing and other safety properties for resource-constrained systems involving autonomy and artificial intelligence on-line. We then describe a vision and agenda for research targeting those challenges.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE 3rd International Conference on Cognitive Machine Intelligence, CogMI 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages163-167
Number of pages5
ISBN (Electronic)9781665416214
DOIs
StatePublished - 2021
Event3rd IEEE International Conference on Cognitive Machine Intelligence, CogMI 2021 - Virtual, Online, United States
Duration: Dec 13 2021Dec 15 2021

Publication series

NameProceedings - 2021 IEEE 3rd International Conference on Cognitive Machine Intelligence, CogMI 2021

Conference

Conference3rd IEEE International Conference on Cognitive Machine Intelligence, CogMI 2021
Country/TerritoryUnited States
CityVirtual, Online
Period12/13/2112/15/21

Keywords

  • AI
  • Autonomy
  • ML
  • neural networks
  • real-time

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Cognitive Neuroscience
  • Artificial Intelligence

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