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Probabilistic Programming Process Algebra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationQuantitative Evaluation of Systems
Subtitle of host publication11th International Conference, QEST 2014, Florence, Italy, September 8-10, 2014. Proceedings
PublisherSpringer International Publishing
Pages249-264
Number of pages16
ISBN (Electronic)978-3-319-10696-0
ISBN (Print)978-3-319-10695-3
DOIs
Publication statusPublished - 8 Sep 2014
Event11th International Conference on Quantit - Florence, Italy
Duration: 8 Sep 201410 Sep 2014

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
Volume8657
ISSN (Print)0302-9743

Conference

Conference11th International Conference on Quantit
CountryItaly
CityFlorence
Period8/09/1410/09/14

Abstract

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 information 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.

Event

11th International Conference on Quantit

8/09/1410/09/14

Florence, Italy

Event: Conference

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