Norm identification in Jason using a bayesian approach

Guilherme Krzisch*, Felipe Meneguzzi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

Abstract

Open multi-agent systems consist of a set of heterogeneous autonomous agents that can enter or leave the system at any time. As they are not necessarily from the same organization, they can have conflicting goals, which can lead them to execute conflicting actions. To prevent these conflicts from negatively impacting the system, a set of expected behaviors – which we refer to as norms – can desirable; to enforce compliance to such norms, sanctioning of violating agents can be used to deter further violations. As new agents enter the system, they must be able to identify existing norms in order to avoid sanctions. In this context, this paper provides two contributions. First, we propose a normative multi-agent system that can be used to evaluate norm-identification algorithms. Second, we validate an existing bayesian norm-identification approach in this system, confirming its positive result in a set of experiments.

Original languageEnglish
Title of host publicationMABS 2017: Multi-Agent Based Simulation XVIII
EditorsGracaliz Pereira Dimuro, Luis Antunes
PublisherSpringer-Verlag
Pages62-73
Number of pages12
ISBN (Print)9783319915869
DOIs
Publication statusPublished - 2018
Event18th International Workshop on Multi-Agent Based Simulation, MABS 2017 - Sao Paulo, Brazil
Duration: 8 May 201712 May 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10798 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Workshop on Multi-Agent Based Simulation, MABS 2017
Country/TerritoryBrazil
CitySao Paulo
Period8/05/1712/05/17

Keywords

  • Multi-agent system
  • Norm identification
  • Normative system

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