Integrated, Distributed Fault Management for Communication Networks

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Apr 26, 1998
Accession Number
ADA440085

Entities

People

  • G. Mykoniatis
  • Huanan Li
  • J. Baras

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Communication Networks
  • Computational Science
  • Control Systems
  • Electrical Engineering
  • Information Science
  • Intelligent Agents
  • Machine Learning
  • Multiagent Systems
  • Networks
  • Neural Networks
  • Probabilistic Models
  • Probability
  • Random Variables
  • Reasoning
  • Reinforcement Learning

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Database Systems and Applications

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms