Bonchi, F;
Silva, A;
Sokolova, A;
(2017)
The power of convex algebras.
In: Meyer, R and Nestmann, U, (eds.)
28th International Conference on Concurrency Theory (CONCUR 2017).
(pp. 23:1-23:18).
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik: Dagstuhl, Germany.
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Abstract
Probabilistic automata (PA) combine probability and nondeterminism. They can be given different semantics, like strong bisimilarity, convex bisimilarity, or (more recently) distribution bisimilarity. The latter is based on the view of PA as transformers of probability distributions, also called belief states, and promotes distributions to first-class citizens. We give a coalgebraic account of the latter semantics, and explain the genesis of the beliefstate transformer from a PA. To do so, we make explicit the convex algebraic structure present in PA and identify belief-state transformers as transition systems with state space that carries a convex algebra. As a consequence of our abstract approach, we can give a sound proof technique which we call bisimulation up-to convex hull.
| Type: | Proceedings paper |
|---|---|
| Title: | The power of convex algebras |
| Event: | 28th International Conference on Concurrency Theory (CONCUR 2017), 5-8 September 2017, Berlin, Germany |
| ISBN-13: | 9783959770484 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.4230/LIPIcs.CONCUR.2017.23 |
| Publisher version: | http://dx.doi.org/10.4230/LIPIcs.CONCUR.2017.23 |
| Language: | English |
| Additional information: | Copyright © Filippo Bonchi, Alexandra Silva, and Ana Sokolova. Licensed under the Creative Commons License CC-BY (https://creativecommons.org/licenses/by/3.0/). |
| Keywords: | belief-state transformers, bisimulation up-to, coalgebra, convex algebra, convex powerset monad, probabilistic automata |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10027982 |
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