Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/3203
Title: A computational model of a norm's yield
Authors: Mahmoud, M. A 
Tang, A. Y. C 
Ahmad, M. S 
Itaiwi, A. M. K 
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference: 2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016 - Bangi, Malaysia 
Abstract: While several works have been conducted on norms detection and identification, almost non-existent work has explored the notion of norm's yield to trigger agents to adopt new norms. In other words, in most of the literature on norms, agents are not aware of the 'yield' or gain from the enacted norms. Instead, they use some mining algorithms to identify the norms from a set of observed events and subsequently adopting the norms without further analysis. Consequently, it would be interesting to look into agents that can deal with norm's yield. In this paper, we propose a computational model of a norm's yield. When an agent could measure a norm's yield, it would have greater reasoning ability about the norm's effects on its performance, which in turn trigger the agent to adopt or reject the norm.
URI: http://dspace.uniten.edu.my:80/jspui/handle/123456789/3203
DOI: 10.1109/ISAMSR.2016.7810014
Appears in Collections:CSIT Scholarly Publication

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