MoULDyS: Monitoring of Autonomous Systems in the Presence of Uncertainties
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914885255823360 |
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| author | Ghosh, Bineet André, Étienne |
| author_facet | Ghosh, Bineet André, Étienne |
| contents | We introduce MoULDyS, that implements efficient offline and online monitoring algorithms of black-box cyber-physical systems w.r.t. safety properties. MoULDyS takes as input an uncertain log (with noisy and missing samples), as well as a bounding model in the form of an uncertain linear system; this latter model plays the role of an over-approximation so as to reduce the number of false alarms. MoULDyS is Python-based and available under the GNU General Public License v3.0 (gpl-3.0). We further provide easy-to-use scripts to recreate the results of two case studies introduced in an earlier work. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_17201 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MoULDyS: Monitoring of Autonomous Systems in the Presence of Uncertainties Ghosh, Bineet André, Étienne Systems and Control We introduce MoULDyS, that implements efficient offline and online monitoring algorithms of black-box cyber-physical systems w.r.t. safety properties. MoULDyS takes as input an uncertain log (with noisy and missing samples), as well as a bounding model in the form of an uncertain linear system; this latter model plays the role of an over-approximation so as to reduce the number of false alarms. MoULDyS is Python-based and available under the GNU General Public License v3.0 (gpl-3.0). We further provide easy-to-use scripts to recreate the results of two case studies introduced in an earlier work. |
| title | MoULDyS: Monitoring of Autonomous Systems in the Presence of Uncertainties |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2407.17201 |