Probabilistic logic programming is increasingly important in artificialintelligence and related fields as a formalism to reason about uncertainty. Itgeneralises logic programming with the possibility of annotating clauses withprobabilities. This paper proposes a coalgebraic semantics on probabilisticlogic programming. Programs are modelled as coalgebras for a certain functor F,and two semantics are given in terms of cofree coalgebras. First, theF-coalgebra yields a semantics in terms of derivation trees. Second, byembedding F into another type G, as cofree G-coalgebra we obtain a `possibleworlds' interpretation of programs, from which one may recover the usualdistribution semantics of probabilistic logic programming. Furthermore, we showthat a similar approach can be used to provide a coalgebraic semantics toweighted logic programming.
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