Probabilistic Graph Programming
نویسندگان
چکیده
We introduce a notion of probability to the graph programming language GP2 which resolves nondeterministic choices of graph transformation rules and their matches. With our programming model Probabilistic GP2 (P-GP2), rule and match decisions are assigned uniform distributions over their domains. In this paper, we present an implementation of P-GP2 as an extension of an existing GP2 compiler. As an example application, we analyse a (polynomial-time) nondeterministic vertex colouring program which may produce one of many possible colourings. The uniform implementation of P-GP2 is shown, by sampling, to produce different colourings with different probabilities, allowing quantities such as expected colouring and likelihood of optimal colouring to be considered.
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