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From Specification Models to Explanation Models: An Extraction and Refinement Process for Timed Automata

Schwammberger, Maike ORCID iD icon; Klös, Verena; Luckcuck, Matt [Hrsg.]; Farrell, Marie [Hrsg.]

Abstract:

Autonomous systems control many tasks in our daily lives. To increase trust in those systems and safety of the interaction between humans and autonomous systems, the system behaviour and reasons for autonomous decision should be explained to users, experts and public authorities. One way to provide such explanations is to use behavioural models to generate context- and user-specific explanations at run-time. However, this comes at the cost of higher modelling effort as additional models need to be constructed. In this paper, we propose a high-level process to extract such explanation models from system models, and to subsequently refine these towards specific users, explanation purposes and situations. By this, we enable the reuse of specification models for integrating self-explanation capabilities into systems. We showcase our approach using a running example from the autonomous driving domain.


Verlagsausgabe §
DOI: 10.5445/IR/1000169854
Veröffentlicht am 11.04.2024
Originalveröffentlichung
DOI: 10.4204/EPTCS.371.2
Scopus
Zitationen: 3
Dimensions
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2075-2180
KITopen-ID: 1000169854
Erschienen in Proceedings of 4th International Workshop on Formal Methods for Autonomous Systems, FMAS@SEFM, Ed.: M. Luckcuck
Veranstaltung 4th International Workshop on Formal Methods for Autonomous Systems (FMAS 2022), Berlin, Deutschland, 26.09.2022 – 27.09.2022
Verlag Open Publishing Association
Seiten 20–37
Serie Electronic proceedings in theoretical computer science ; 371
Vorab online veröffentlicht am 28.09.2022
Nachgewiesen in Scopus
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