RankPL: A Qualitative Probabilistic Programming Language

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Rienstra, Tjitze;
  • Subject: Computer Science - Programming Languages | Computer Science - Artificial Intelligence

In this paper we introduce RankPL, a modeling language that can be thought of as a qualitative variant of a probabilistic programming language with a semantics based on Spohn's ranking theory. Broadly speaking, RankPL can be used to represent and reason about processes ... View more
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  • Related Research Results (1)
    Inferred by OpenAIRE
    RankPL software on GitHub
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