MDWNsolver: A Framework to Design and Solve Markov Decision Petri Nets

نویسندگان

  • MARCO BECCUTI
  • Marco Beccuti
  • Giuliana Franceschinis
  • Serge Haddad
چکیده

MDWNsolver is a framework for system modeling and optimization of performability measures based on Markov Decision Petri Net (MDPN) and Markov Decision Well-formed Net (MDWN) formalisms, two Petri Net extensions for high level specification of Markov Decision Processes (MDP). It is integrated in the GreatSPN suite which provides a GUI to design MDPN/MDWN models. From the analysis point of view, MDWNsolver uses efficient algorithms that take advantage of system symmetries, thus reducing the analysis complexity. In this paper the MDWNsolver framework features and architecture are presented, and some application examples are discussed.

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تاریخ انتشار 2011