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21 A.I. & L. 1 (2013)

handle is hein.journals/artinl21 and id is 1 raw text is: Artif Intell Law (2013) 21:1-46 DOI 10.1007/s10506-012-9126-7 Identifying prohibition norms in agent societies Bastin Tony Roy Savarimuthu - Stephen Cranefield Maryam A. Purvis - Martin K. Purvis Published online: 23 August 2012 © Springer Science+Business Media B.V. 2012 Abstract In normative multi-agent systems, the question of how an agent identifies norms in an open agent society has not received much attention. This paper aims at addressing this question. To this end, this paper proposes an architecture for norm identification for an agent. The architecture is based on observation of interactions between agents. This architecture enables an autonomous agent to identify prohibition norms in a society using the prohibition norm identification (PNI) algorithm. The PNI algorithm uses association rule mining, a data mining approach to identify sequences of events as candidate norms. When a norm changes, an agent using our architecture will be able to modify the norm and also remove a norm if it does not hold in the society. Using simulations of a park scenario we demonstrate how an agent makes use of the norm identification framework to identify prohibition norms. Keywords Norms - Agents - Architecture - Norm identification Prohibition norms - Simulation - Societies - Normative multi-agent systems (NorMAS) 1 Introduction No other concept is invoked by social scientists more frequently than that of norms (Sills 1968). In human societies, norms have played an important role in regulating the behaviour of the individuals in a society. For example, regulation of behaviour in public spaces such as parks and restaurants is governed by norms. It is expected that no one litters a park. In a restaurant it is expected that no one smokes1 This is true in most countries. B. T. R. Savarimuthu (E) - S. Cranefield - M. A. Purvis - M. K. Purvis University of Otago, Dunedin, New Zealand e-mail: tonyr@infoscience.otago.ac.nz I_ Springer

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