Reaching Out Towards Fully Verified Autonomous Systems

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Abstract

Autonomous systems such as “self-driving” vehicles and closed-loop medical devices increasingly rely on learning-enabled components such as neural networks to perform safety critical perception and control tasks. As a result, the problem of verifying that these systems operate correctly is of the utmost importance. We will briefly examine the role of neural networks in the design and implementation of autonomous systems, and how various verification approaches can contribute towards engineering verified autonomous systems. In doing so, we examine promising initial solutions that have been proposed over the past three years and the big challenges that remain to be tackled.

Original languageEnglish
Title of host publicationReachability Problems - 13th International Conference, RP 2019, Proceedings
EditorsEmmanuel Filiot, Raphaël Jungers, Igor Potapov
PublisherSpringer Verlag
Pages22-32
Number of pages11
ISBN (Print)9783030308056
DOIs
Publication statusPublished - 1 Jan 2019
Event13th International Conference on Reachability Problems, RP 2019 - Brussels, Belgium
Duration: 11 Sept 201913 Sept 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11674 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Reachability Problems, RP 2019
Country/TerritoryBelgium
CityBrussels
Period11/09/1913/09/19

Keywords

  • Autonomous systems
  • Constraint solvers
  • Formal verification

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