NormLab: A framework to support research on norm synthesis

Javier Morales, Iosu Mendizabal, David Sánchez-Pinsach, Maite Lopez-Sanchez, Michael Wooldridge, Wamberto Vasconcelos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

MAS research has investigated norms as a means to coordinate open multi-agent systems (MAS). This has spurred a strand of research on on-line norm synthesis algorithms for MASs. However, to the best of our knowledge, currently there is no computational framework to support the development and study of on-line norm synthesis. Here we present NORMLAB, a novel framework to support norm synthesis research, highlighting its important features. We also outline the operation of two novel on-line norm synthesis strategies, which significantly outperform the state of the art.

Original languageEnglish
Title of host publicationAAMAS '14 Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems
EditorsAna Bazzan, Michael Huhns, Alessio Lomuscio, Paul Scerri
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1697-1698
Number of pages2
Volume2
ISBN (Electronic)9781634391313
ISBN (Print)9781450327381
Publication statusPublished - 10 May 2014
Event13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 - Paris, France
Duration: 5 May 20149 May 2014

Conference

Conference13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
CountryFrance
CityParis
Period5/05/149/05/14

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Morales, J., Mendizabal, I., Sánchez-Pinsach, D., Lopez-Sanchez, M., Wooldridge, M., & Vasconcelos, W. (2014). NormLab: A framework to support research on norm synthesis. In A. Bazzan, M. Huhns, A. Lomuscio, & P. Scerri (Eds.), AAMAS '14 Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems (Vol. 2, pp. 1697-1698). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). https://dl.acm.org/citation.cfm?id=2616131