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 language | English |
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Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Publisher | Springer Verlag |
Pages | 242-255 |
Number of pages | 14 |
DOIs | |
State | Published - 2019 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11500 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.
Funders | Funder number |
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Israel Science Foundation | 1464/18 |