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A regulative norms mining algorithm for complex adaptive system

Adaptive systems; Soft computing; Complex adaptive systems; Exceptional events; Mining algorithms; Normative system; Norms identifications; Regulative norms; Social norm; Data mining

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Main Authors: Mahmoud M.A., Ahmad M.S., Yusoff M.Z.M., Mostafa S.A.
Other Authors: 55247787300
Format: Conference Paper
Published: Springer Verlag 2023
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id my.uniten.dspace-24221
record_format dspace
spelling my.uniten.dspace-242212023-05-29T14:57:07Z A regulative norms mining algorithm for complex adaptive system Mahmoud M.A. Ahmad M.S. Yusoff M.Z.M. Mostafa S.A. 55247787300 56036880900 22636590200 37036085800 Adaptive systems; Soft computing; Complex adaptive systems; Exceptional events; Mining algorithms; Normative system; Norms identifications; Regulative norms; Social norm; Data mining In complex adaptive system, a visitor agent is not usually and explicitly given the norms of its host agent. Thus, when it is not able to adapt the host agent�s norms, it is totally deprived of accessing resources and services from the host. Such circumstance severely affects its performance resulting in failure to achieve its goal. Consequently, this paper attempts to resolve the problem by enabling the agent to identify the host�s regulative norms via an algorithm called the Regulative Norms Mining Algorithm (RNMA). Regulative norms constitute the recommendation, obligation, and prohibition norms, which the RNMA identifies by analyzing exceptional events that trigger rewards or penalties. In this paper, we argue that existing norms identifications algorithms are inadequate to detect different regulative norm types. Consequently, we propose the RNMA algorithm, which could alleviate the problem. We demonstrate the merit of the algorithm by apply it on a typical scenario. � 2018, Springer International Publishing AG. Final 2023-05-29T06:57:07Z 2023-05-29T06:57:07Z 2018 Conference Paper 10.1007/978-3-319-72550-5_21 2-s2.0-85041554080 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041554080&doi=10.1007%2f978-3-319-72550-5_21&partnerID=40&md5=7c86dfddcafe9af893ddf0646adebc1c https://irepository.uniten.edu.my/handle/123456789/24221 700 213 224 Springer Verlag Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Adaptive systems; Soft computing; Complex adaptive systems; Exceptional events; Mining algorithms; Normative system; Norms identifications; Regulative norms; Social norm; Data mining
author2 55247787300
author_facet 55247787300
Mahmoud M.A.
Ahmad M.S.
Yusoff M.Z.M.
Mostafa S.A.
format Conference Paper
author Mahmoud M.A.
Ahmad M.S.
Yusoff M.Z.M.
Mostafa S.A.
spellingShingle Mahmoud M.A.
Ahmad M.S.
Yusoff M.Z.M.
Mostafa S.A.
A regulative norms mining algorithm for complex adaptive system
author_sort Mahmoud M.A.
title A regulative norms mining algorithm for complex adaptive system
title_short A regulative norms mining algorithm for complex adaptive system
title_full A regulative norms mining algorithm for complex adaptive system
title_fullStr A regulative norms mining algorithm for complex adaptive system
title_full_unstemmed A regulative norms mining algorithm for complex adaptive system
title_sort regulative norms mining algorithm for complex adaptive system
publisher Springer Verlag
publishDate 2023
_version_ 1806423497680879616
score 13.222552

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