Automatic Symbolic Solution of Markov Chains.

Abstract

Continuous time Markov chains are commonly used in system performance modeling. Increasing system complexity and non-Markovian behavior can drastically increase the size of a Markov model's state space. Accordingly, approximation techniques have been introduced to reduce the resources needed to solve Markov chain models. In this paper the authors discuss a method for automatically deriving symbolic solutions of Markov chains. Symbolic solutions should provide insight when attempting to evaluate the validity of both Markov models and approximation techniques for their solution. (Author).

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA150476

Entities

People

  • A. Reibman
  • K. Trivedi
  • R. Marie

Organizations

  • Duke University

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Classification
  • Computer Science
  • Computers
  • Differential Equations
  • Equations
  • Integral Equations
  • Markov Chains
  • Markov Models
  • Markov Processes
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Reliability
  • Simulations
  • Stochastic Processes
  • Test And Evaluation
  • Universities

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • Space