The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article présente un cadre pour automatiser la gestion des pannes à l'aide d'agents logiciels distribués. La fonction de gestion est répartie entre plusieurs agents pouvant effectuer des activités de raisonnement avancées sur le domaine réseau. La modélisation du domaine réseau utilisant le réseau bayésien est introduite. L'agent détecte, corrèle et cherche sélectivement à dériver une explication claire des alarmes générées dans son domaine. Selon le degré d'automatisation du réseau, l'agent peut même réaliser des actions de restauration locales. Les idées de l'article sont implémentées dans un logiciel d'inférence dans un réseau bayésien. Nous identifions les potentialités d'apprentissage dans le modèle agent et présentons la classe de problèmes à résoudre.
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Hassan HAJJI, Behrouz Homayoun FAR, "Distributed Software Agents for Network Fault Management" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 4, pp. 735-746, April 2000, doi: .
Abstract: This paper discusses a framework for automating fault management using distributed software agents. The management function is distributed among multiple agents that can carry out advanced reasoning activities on the network domain. Network domain modeling using Bayesian network is introduced. The agent detects, correlates and selectively seeks to derive a clear explanation of the alarms generated in its domain. Depending on the network's degree of automation, the agent can even carry out local recovery actions. The ideas of the paper are implemented in a software for inference in Bayesian network. We identify the potentialities of learning in the agent model, and present the class of problems to be addressed.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_4_735/_p
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@ARTICLE{e83-d_4_735,
author={Hassan HAJJI, Behrouz Homayoun FAR, },
journal={IEICE TRANSACTIONS on Information},
title={Distributed Software Agents for Network Fault Management},
year={2000},
volume={E83-D},
number={4},
pages={735-746},
abstract={This paper discusses a framework for automating fault management using distributed software agents. The management function is distributed among multiple agents that can carry out advanced reasoning activities on the network domain. Network domain modeling using Bayesian network is introduced. The agent detects, correlates and selectively seeks to derive a clear explanation of the alarms generated in its domain. Depending on the network's degree of automation, the agent can even carry out local recovery actions. The ideas of the paper are implemented in a software for inference in Bayesian network. We identify the potentialities of learning in the agent model, and present the class of problems to be addressed.},
keywords={},
doi={},
ISSN={},
month={April},}
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TY - JOUR
TI - Distributed Software Agents for Network Fault Management
T2 - IEICE TRANSACTIONS on Information
SP - 735
EP - 746
AU - Hassan HAJJI
AU - Behrouz Homayoun FAR
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2000
AB - This paper discusses a framework for automating fault management using distributed software agents. The management function is distributed among multiple agents that can carry out advanced reasoning activities on the network domain. Network domain modeling using Bayesian network is introduced. The agent detects, correlates and selectively seeks to derive a clear explanation of the alarms generated in its domain. Depending on the network's degree of automation, the agent can even carry out local recovery actions. The ideas of the paper are implemented in a software for inference in Bayesian network. We identify the potentialities of learning in the agent model, and present the class of problems to be addressed.
ER -