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Algorithm 972: JMarkov: An integrated framework for Markov chain modeling

Markov chains (MC) are a powerful tool for modeling complex stochastic systems. Whereas a number of tools exist for solving different types ofMCmodels, the first step inMCmodeling is to define themodel parameters. This step is, however, error prone and far from trivial when modeling complex systems....

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Detalles Bibliográficos
Autores Principales: Pérez, Juan F., Silva D.F., Góez J.C., Riaño G., Sarmiento A., Sarmiento-Romero A., Akhavan-Tabatabaei R.
Formato: Artículo (Article)
Lenguaje:Inglés (English)
Publicado: Association for Computing Machinery 2017
Materias:
Chains
Queueing theory
Stochastic models
Stochastic systems
Exponential distributions
Infinite state space
Integrated frameworks
Markov Decision Processes
Optimal decision-rule
Phase type distributions
Quasi-birth and death process
Steady state and transients
Markov processes
Markov chains
Markov decision processes
Phase-type distributions
Quasi-birth-and-death processes
Stochastic modeling
Acceso en línea:https://repository.urosario.edu.co/handle/10336/23121
https://doi.org/10.1145/3009968

Internet

https://repository.urosario.edu.co/handle/10336/23121
https://doi.org/10.1145/3009968

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