Print Email Facebook Twitter Data-Driven Revision of Conditional Norms in Multi-Agent Systems Title Data-Driven Revision of Conditional Norms in Multi-Agent Systems Author Dell'Anna, D. (TU Delft Control & Simulation) Alechina, Natasha (Universiteit Utrecht) Dalpiaz, Fabiano (Universiteit Utrecht) Dastani, Mehdi (Universiteit Utrecht) Logan, Brian (Universiteit Utrecht; University of Aberdeen) Date 2023 Abstract In multi-agent systems, norm enforcement is a mechanism for steering the behavior of individual agents in order to achieve desired system-level objectives. Due to the dynamics of multi-agent systems, however, it is hard to design norms that guarantee the achievement of the objectives in every operating context. Also, these objectives may change over time, thereby making previously defined norms ineffective. In this paper, we investigate the use of system execution data to automatically synthesise and revise conditional prohibitions with deadlines, a type of norms aimed at prohibiting agents from exhibiting certain patterns of behaviors. We propose DDNR (Data-Driven Norm Revision), a data-driven approach to norm revision that synthesises revised norms with respect to a data set of traces describing the behavior of the agents in the system. We evaluate DDNR using a state-of-the-art, off-the-shelf urban traffic simulator. The results show that DDNR synthesises revised norms that are significantly more accurate than the original norms in distinguishing adequate and inadequate behaviors for the achievement of the system-level objectives. To reference this document use: http://resolver.tudelft.nl/uuid:7cd949ea-94d9-4fb7-8f5a-f93d6676ff3f DOI https://doi.org/10.1613/jair.1.13683 Embargo date 2023-09-01 ISSN 1076-9757 Source The Journal of Artificial Intelligence Research, 75, 1549-1593 Bibliographical note Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2023 D. Dell'Anna, Natasha Alechina, Fabiano Dalpiaz, Mehdi Dastani, Brian Logan Files PDF DellAnna_DDNR.pdf 1.14 MB Close viewer /islandora/object/uuid:7cd949ea-94d9-4fb7-8f5a-f93d6676ff3f/datastream/OBJ/view