Probabilistic concurrent constraint programming

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Abstract

We extend co to allow the specification of a discrete probability distribution for random variables. We demonstrate the expressiveness of pcc by synthesizing combinators for default reasoning. We extend pcc uniformly over time, to get a synchronous reactive probabilistic programming language, timed pcc. We describe operational and denotational models for pcc (and Timed pcc). The key feature of the denotational model(s) is that parallel composition is essentially set intersection. We show that the denotational model of pco (resp. Timed pcc) is conservative over cc (resp. tcc). We also show that the denotational models are fully abstract for an operational semantics that records probability information.

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Gupta, V., Jagadeesan, R., & Saraswat, V. (1997). Probabilistic concurrent constraint programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1243, pp. 243–257). Springer Verlag. https://doi.org/10.1007/3-540-63141-0_17

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