Obligation Norm Identification in Agent Societies

Tony Bastin Roy Savarimuthu (), Stephen Cranefield (), Maryam A. Purvis () and Martin K. Purvis ()
Additional contact information
Stephen Cranefield: http://infosci.otago.ac.nz/stephen-cranefield/
Maryam A. Purvis: http://www.infosci.otago.ac.nz/maryam-purvis/
Martin K. Purvis: http://waitaki.otago.ac.nz/~martin/

Journal of Artificial Societies and Social Simulation, 2010, vol. 13, issue 4, 3

Abstract: Most works on norms have investigated how norms are regulated using institutional mechanisms. Very few works have focused on how an agent may infer the norms of a society without the norm being explicitly given to the agent. This paper describes a mechanism for identifying one type of norm, an obligation norm. The Obligation Norm Inference (ONI) algorithm described in this paper makes use of an association rule mining approach to identify obligation norms. Using agent based simulation of a virtual restaurant we demonstrate how an agent can identify the tipping norm. The experiments that we have conducted demonstrate that an agent in the system is able to add, remove and modify norms dynamically. An agent can also flexibly modify the parameters of the system based on whether it is successful in identifying a norm.

Keywords: Norms; Social Norms; Obligations; Norm Identification; Agent-Based Simulation; Simulation of Norms; Artificial Societies; Normative Multi-Agent Systems (NorMAS) (search for similar items in EconPapers)
Date: 2010-10-31
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2010-13-2

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