Control synthesis through deep learning

Doron Peled, Simon Iosti, Saddek Bensalem

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

Deep learning has gained unprecedented rapid popularity in computer science in recent years. It is used in tasks that were previously considered highly challenging for computers, such as speech and image recognition and natural language processing. While deep learning is often associated with complicated tasks, we look at the much more mundane task of refining a system behavior through control that is constructed with the use of learning techniques. We compare the use of deep learning for this task with other techniques such as automata learning and genetic programming.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages242-255
Number of pages14
DOIs
StatePublished - 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11500 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Funding

D. Peled–The research performed by this author was partially funded by Israeli Science Foundation grant 1464/18: “Efficient Runtime Verification for Systems with Lots of Data and its Applications”.. Acknowledgement. The authors would like to thank Yoav Goldberg, for useful discussions on deep learning and comments on an early draft of the paper.

FundersFunder number
Israel Science Foundation1464/18

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