Authors:
Muhsen Hammoud
;
Alicia Y. C. Tang
and
Azhana Ahmad
Affiliation:
Universiti Tenaga Nasional, Malaysia
Keyword(s):
Social Norms, Normative Multi-agent Systems, Negative Norms, Norms Detection.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Computational Intelligence
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation and Reasoning
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Self Organizing Systems
;
Soft Computing
;
Software Engineering
;
Symbolic Systems
Abstract:
Social norms main objective is to regulate autonomous agents’ behaviour in an open normative multi-agent
system. Norms in these societies are dynamically created and disappeared according to the society’s needs.
Consequently, norms effects on agents or on the environment are not observable at the moment of creation.
Norms practicing consequences might be either positive, like increasing the educational level of a society by
conducting social discussions. Or negative, like causing money loss in gambling. Or the norm might have
neutral consequences. In this paper, we propose a technique to detect negative norms in an open normative
multi-agent system. Our technique has two main stages: i) Observation and ii) Analysis. The observation
stage relies on the overhearing approach of monitoring where the messages that are exchanged between
agents are observable. All observations are then analysed in order to detect negative norms. Negativity of a
norm is based on its effect on agents or on th
e environment. In this technique, we adopted ATN concept to
represent norms. This technique is implemented using Java and JADE. Testing results of this technique
shows that it works properly, and detects negative norms according to the defined negativity threshold.
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