Norm mining, identification, and detection: a systematic literature review
This paper presents a systematic literature review on norm identification in multi-agent systems. Norms play a crucial role in guiding agent behavior, ensuring cooperation, and resolving conflicts. By analyzing 35 selected studies, we categorize methods for detecting, synthesizing, and adapting norms in multi-agent systems. We also examine their effectiveness in dynamic and uncertain environments. The findings highlight gaps in current approaches, including scalability, adaptability, and real-world applicability. Future directions emphasize the integration of Large Language Models, testing in complex environments, and fostering interdisciplinary collaboration to advance socially aware autonomous systems.
Authors
- Yazan Mualla (ORCID: https://orcid.org/0000-0002-6772-6135)
- Amro Najjar
- Vincent de Wit (ORCID: https://orcid.org/0000-0002-2664-9209)
- Sukriti Bhattacharya
- Igor Tchappi
- Benoît Alcaraz
Institutions
- University of Luxembourg (LU)
- Université de technologie de belfort-montbéliard (FR)
- Luxembourg Institute of Science and Technology (LU)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2026-02-26
- DOI
- https://doi.org/10.3389/frai.2026.1702659
- Primary Topic
- Multi-Agent Systems and Negotiation
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fonds National de la Recherche Luxembourg