Abstract
This paper presents some aspects of the “Réseau futé (Smart Net)” project, whose aim is to introduce Artificial Intelligence techniques (such as machine learning and multi-agent systems) in network management and supervision, in order to help the processing of the large volume of events notifications received by network management operators. We provide experimental and theoretical results on learning patterns called chronicles in order to design a machine assistant to network operators. Theoretical results investigate different levels of help that could be brought by the operator to the assistant. The tests were performed in two distinct realworld situations. They showed the circumstances under which chronicle learning is possible without the help of the operator or another assistant.
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© 1997 Springer Science+Business Media New York
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Quinqueton, J., Esfandiari, B., Nock, R. (1997). Chronicle Learning and Agent oriented techniques for network management and supervision. In: Gaïti, D. (eds) Intelligent Networks and Intelligence in Networks. IFIP — The International Federation for Information Processing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35323-4_10
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DOI: https://doi.org/10.1007/978-0-387-35323-4_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-5543-5
Online ISBN: 978-0-387-35323-4
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