TY - GEN
T1 - Norm identification in Jason using a bayesian approach
AU - Krzisch, Guilherme
AU - Meneguzzi, Felipe
N1 - Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Multi-agent system
KW - Norm identification
KW - Normative system
UR - http://www.scopus.com/inward/record.url?scp=85047335411&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-91587-6_5
DO - 10.1007/978-3-319-91587-6_5
M3 - Published conference contribution
AN - SCOPUS:85047335411
SN - 9783319915869
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 62
EP - 73
BT - MABS 2017: Multi-Agent Based Simulation XVIII
A2 - Dimuro, Gracaliz Pereira
A2 - Antunes, Luis
PB - Springer-Verlag
T2 - 18th International Workshop on Multi-Agent Based Simulation, MABS 2017
Y2 - 8 May 2017 through 12 May 2017
ER -