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Poster communications

Graphically explaining norms

Madalina Croitoru 1 Oren Nir 2 Miles Simon 2 Luck Michael 2 
1 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : While much work has focused on the creation of norm aware agents, much less has been concerned with aiding a system designers in understanding the effects of norms on a system. However, since norms are generally pre-determined by designers, providing such support can be critical in enabling norm refinement for more effective or efficient system regulation. In this paper, we address just this problem by providing explanations as to why some norm is applicable, violated, or in some other state. We make use of conceptual graph based semantics to provide an easily interpretable graphical representation of the norms within a system.Such a representation allows for visual explanation of the state of norms, showing for example why they may have been activated or violated. Such an explanation enables easy understanding of the system operation without needing to follow the system's underlying logic.
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Poster communications
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Submitted on : Monday, November 22, 2010 - 2:03:01 PM
Last modification on : Friday, August 5, 2022 - 3:03:00 PM
Long-term archiving on: : Wednesday, February 23, 2011 - 3:22:57 AM


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  • HAL Id : lirmm-00538391, version 1
  • PRODINRA : 246677



Madalina Croitoru, Oren Nir, Miles Simon, Luck Michael. Graphically explaining norms. Wiebe van der Hoek; Gal A. Kaminka; Yves Lespérance; Michael Luck; Sandip Sen. AAMAS: Autonomous Agents and Multiagent Systems, 2010, Toronto, Canada. IFAAMAS 2010, 9th International Conference on Autonomous Agents and Multiagent Systems, 1, pp.1405-1406, 2010, AAMAS'10: 9th International Conference on Autonomous Agents and Multiagent Systems. ⟨lirmm-00538391⟩



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