Probabilistic Programming Process Algebra [chapter]

Anastasis Georgoulas, Jane Hillston, Dimitrios Milios, Guido Sanguinetti
2014 Lecture Notes in Computer Science  
Formal modelling languages such as process algebras are widespread and effective tools in computational modelling. However, handling data and uncertainty in a statistically meaningful way is an open problem in formal modelling, severely hampering the usefulness of these elegant tools in many real world applications. Here we introduce ProPPA, a process algebra which incorporates uncertainty in the model description, allowing the use of Machine Learning techniques to incorporate observational
more » ... rmation in the modelling. We define the semantics of the language by introducing a quantitative generalisation of Constraint Markov Chains. We present results from a prototype implementation of the language, demonstrating its usefulness in performing inference in a non-trivial example.
doi:10.1007/978-3-319-10696-0_21 fatcat:vkqzg5d5dzafpoon73oi2xd4ze