Probabilistic Concurrent Constraint Programming
Vineet Gupta, Radha Jagadeesan, Vijay A. Saraswat
Abstract
We extend cc to allow the specification of a discrete probability
distribution for random variables. We demonstrate the expressiveness
of Probabilistic cc by synthesizing combinators for default reasoning. We
extend Probabilistic cc uniformly over time, to get a synchronous reactive
probabilistic programming language, Timed Probabilistic cc .
We describe operational and denotational models for Probabilistic cc
(and Timed Probabilistic cc ). The key feature of the denotational
model(s) is that parallel composition is essentially set intersection.
We show that the denotational model of Probabilistic cc (resp. Timed
Probabilistic cc ) is conservative over cc (resp. Timed cc ). We also
show that the denotational models are fully abstract for an
operational semantics that records probability information.
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