Norm identification in Jason using a bayesian approach

Guilherme Krzisch; Felipe Meneguzzi

doi:10.1007/978-3-319-91587-6_5

Norm identification in Jason using a bayesian approach

Guilherme Krzisch^*, Felipe Meneguzzi

^*Corresponding author for this work

Computing Science

Pontifícia Universidade Católica do Rio Grande do Sul

Research output: Chapter in Book/Report/Conference proceeding › Published 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 language	English
Title of host publication	MABS 2017: Multi-Agent Based Simulation XVIII
Editors	Gracaliz Pereira Dimuro, Luis Antunes
Publisher	Springer-Verlag
Pages	62-73
Number of pages	12
ISBN (Print)	9783319915869
DOIs	https://doi.org/10.1007/978-3-319-91587-6_5
Publication status	Published - 2018
Event	18th International Workshop on Multi-Agent Based Simulation, MABS 2017 - Sao Paulo, Brazil Duration: 8 May 2017 → 12 May 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10798 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Workshop on Multi-Agent Based Simulation, MABS 2017
Country/Territory	Brazil
City	Sao Paulo
Period	8/05/17 → 12/05/17

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.

Keywords

Multi-agent system
Norm identification
Normative system

Access to Document

10.1007/978-3-319-91587-6_5

Cite this

Krzisch, G., & Meneguzzi, F. (2018). Norm identification in Jason using a bayesian approach. In G. P. Dimuro, & L. Antunes (Eds.), MABS 2017: Multi-Agent Based Simulation XVIII (pp. 62-73). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10798 LNAI). Springer-Verlag. https://doi.org/10.1007/978-3-319-91587-6_5

Norm identification in Jason using a bayesian approach. / Krzisch, Guilherme; Meneguzzi, Felipe.
MABS 2017: Multi-Agent Based Simulation XVIII. ed. / Gracaliz Pereira Dimuro; Luis Antunes. Springer-Verlag, 2018. p. 62-73 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10798 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Krzisch, G & Meneguzzi, F 2018, Norm identification in Jason using a bayesian approach. in GP Dimuro & L Antunes (eds), MABS 2017: Multi-Agent Based Simulation XVIII. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10798 LNAI, Springer-Verlag, pp. 62-73, 18th International Workshop on Multi-Agent Based Simulation, MABS 2017, Sao Paulo, Brazil, 8/05/17. https://doi.org/10.1007/978-3-319-91587-6_5

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Norm identification in Jason using a bayesian approach

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Keywords

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