We describe a mathematical structure that can give extensional denotational semantics to higher-order probabilistic programs. It is not limited to discrete probabilities, and it is compatible with integration in a way the models that have been proposed before are not. It is organised as a model of propositional linear logic in which all the connectives have intuitive probabilistic interpretations. In addition, it has least fixed points for all maps, so it can interpret recursion.
翻译:我们描述一个数学结构,它可以给高阶概率程序提供扩展的分解语义语义。 它不仅限于离散概率,而且与整合不相容,与以前提出的模型不相容。 它被组织成一种推论线性逻辑模型,所有连接者都具有直觉概率解释。 此外,它对所有地图都拥有最小的固定点,因此可以解释循环。