Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Author: search.filters.author.Baras, John S.Subject: search.filters.subject.belief networks

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    Intelligent Distributed Fault Management for Communication Networks
    (2000) Li, Hongjun; Baras, John S.; ISR; CSHCN
    In this paper, we present an intelligent, distributed fault management system for communication networks using belief networks as fault model and inference engine. The managed network is divided into domains and for each domain, there is an intelligent agent called Domain Diagnostic Agent attached to it, which is responsible for this domain's fault management. Belief network models are embedded in such an agent and under symptoms observation, the posterior probabilities of each candidate fault node being faulty is computed. We define the notion of right diagnosis, describe the diagnosis process based on this concept, and present a strategy for generation of test sequence.
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    An Automated, Distributed, Intelligent Fault Management System for Communication Networks
    (1999) Li, Hongjun; Baras, John S.; Mykoniatis, George; ISR; CSHCN
    In this paper we present a Distributed Intelligent Fault Management (DIFM) system for communication networks. The overall architecture of the proposed system is based on a distributed, cooperative, multi-agent paradigm, with probabilistic networks as the framework for knowledge representation and evidence inferencing. We adopt the management by delegation paradigm for network monitoring and integrate both hard and soft faults.
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    Integrated, Distributed Fault Management for Communication Networks
    (1998) Baras, John S.; Li, Hongjun; Mykoniatis, G.; Baras, John S.; ISR; CSHCN
    This report describes an integrated, distributed fault management (IDFM) system for communication networks. The architecture is based on a distributed intelligent agent paradigm, with probabilistic networks as the framework for knowledge representation and evidence inferencing. A static strategy for generating the suggestive test sequence is proposed, based on which a heuristic dynamic strategy is initiated. Another dynamic strategy, formulated as a Markov decision problem, is also provided. To solve this problem, reinforcement learning techniques are investigated.