Norm mining, identification, and detection: a systematic literature review
Benoît Alcaraz1, Yazan Mualla2, Sukriti Bhattacharya3
1Department of Computer Science, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Abstract:
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.
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