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EnglishWe address the problem of verifying timed properties of Markovian models of large populations of interacting agents, modelled as finite state automata. In particular, we focus on time-bounded properties of (random) individual agents specified by Deterministic Timed Automata (DTA) endowed with a single clock. Exploiting ideas from fluid approximation, we estimate the satisfaction probability of the DTA properties by reducing it to the computation of the transient probability of a subclass of Time-Inhomogeneous Markov Renewal Processes with exponentially and deterministically-timed transitions, and a small state space. For this subclass of models, we show how to derive a set of Delay Differential Equations (DDE), whose numerical solution provides a fast and accurate estimate of the satisfaction probability. In the paper, we also prove the asymptotic convergence of the approach, and exemplify the method on a simple epidemic spreading model. Finally, we also show how to construct a system of DDEs to efficiently approximate the average number of agents that satisfy the DTA specification.
| Titolo: | Fluid model checking of timed properties | |
| Autori: | ||
| Data di pubblicazione: | 2015 | |
| Rivista: | ||
| Abstract: | We address the problem of verifying timed properties of Markovian models of large populations of interacting agents, modelled as finite state automata. In particular, we focus on time-bounded properties of (random) individual agents specified by Deterministic Timed Automata (DTA) endowed with a single clock. Exploiting ideas from fluid approximation, we estimate the satisfaction probability of the DTA properties by reducing it to the computation of the transient probability of a subclass of Time-Inhomogeneous Markov Renewal Processes with exponentially and deterministically-timed transitions, and a small state space. For this subclass of models, we show how to derive a set of Delay Differential Equations (DDE), whose numerical solution provides a fast and accurate estimate of the satisfaction probability. In the paper, we also prove the asymptotic convergence of the approach, and exemplify the method on a simple epidemic spreading model. Finally, we also show how to construct a system of DDEs to efficiently approximate the average number of agents that satisfy the DTA specification. | |
| Handle: | http://hdl.handle.net/11368/2856186 | |
| ISBN: | 9783319229744 | |
| URL: | http://springerlink.com/content/0302-9743/copyright/2005/ | |
| Appare nelle tipologie: | 4.1 Contributo in Atti Convegno (Proceeding) |
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| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| FORMATS2015-post.pdf | post-print | Bozza finale post-referaggio (post-print) | Digital Rights Management non definito | Open Access Visualizza/Apri |
| FORMATS2015.pdf | Documento in Versione Editoriale | Digital Rights Management non definito | Administrator Richiedi una copia |
http://hdl.handle.net/11368/2856186
