Publication: A computational model of a norm's yield
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Date
2017
Authors
Itaiwi A.-M.K.
Ahmad M.S.
Tang A.Y.C.
Mahmoud M.A.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
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. � 2016 IEEE.
Description
Computation theory; Computational methods; Robotics; Computational model; Mining algorithms; norm benefits; norm yield; Normative agents; Norms detections; Reasoning ability; Multi agent systems