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  4. Formal Specification for Learning-Enabled Autonomous Systems
 
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2022
Conference Paper
Titel

Formal Specification for Learning-Enabled Autonomous Systems

Abstract
The formal specification provides a uniquely readable description of various aspects of a system, including its temporal behavior. This facilitates testing and sometimes automatic verification of the system against the given specification. We present a logic-based formalism for specifying learning-enabled autonomous systems, which involve components based on neural networks. The formalism is based on first-order past time temporal logic that uses predicates for denoting events. We have applied the formalism successfully to two complex use cases.
Author(s)
Bensalem, Saddek
University Grenoble Alpes
Cheng, Chih-Hong
Fraunhofer-Institut für Kognitive Systeme IKS
Huang, Xiaowei
University of Liverpool
Katsaros, Panagiotis
Aristotle University of Thessaloniki
Molin, Adam
Denso Automotive
Nickovic, Dejan
Austrian Institute of Technology
Peled, Doron
Bar Ilan University
Hauptwerk
Software Verification and Formal Methods for ML-Enabled Autonomous Systems
Konferenz
International Workshop on Formal Methods for ML-Enabled Autonomous Systems 2022
International Workshop on Numerical Software Verification 2022
International Conference on Computer-Aided Verification 2022
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DOI
10.1007/978-3-031-21222-2_8
Language
English
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Fraunhofer-Institut für Kognitive Systeme IKS
Tags
  • autonomous systems

  • learning-enabled systems

  • formal specification

  • neural networks

  • first-order LTL

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