LFCS seminar: Anastasis Georgoulas: Probabilistic programming process algebra
What 


When 
Nov 15, 2016 from 04:00 PM to 05:00 PM 
Where  IF 4.31/4.33 
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Stochastic processes such as Continuous Time Markov Chains are often used to model natural or engineered systems. A large class of languages, such as process algebras, have been developed to formally describe and analyse such systems, but are not applicable when our knowledge of the system is incomplete, as is often the case. On the other hand, the probabilistic programming paradigm is currently receiving much attention as a way of describing probabilistic models and automatically applying sophisticated inference algorithms to match observed behaviour; however, existing languages are not wellsuited to dynamical systems. In this talk, I will present the work of my PhD, particularly the definition of ProPPA  a modelling language incorporating aspects of probabilistic programming into the framework of process algebras. The idea behind the language is to enable the formal description of Markovian stochastic systems with uncertainty, as well as the statistical inference of their parameters based on observed data. I will discuss the implications that introducing uncertainty into the system description has on the syntax and, particularly, the semantics of the language.
(joint work with Jane Hillston and Guido Sanguinetti)