3 research outputs found
Exploiting parallelism in coalgebraic logic programming
We present a parallel implementation of Coalgebraic Logic Programming (CoALP)
in the programming language Go. CoALP was initially introduced to reflect
coalgebraic semantics of logic programming, with coalgebraic derivation
algorithm featuring both corecursion and parallelism. Here, we discuss how the
coalgebraic semantics influenced our parallel implementation of logic
programming
Coalgebraic Semantics for Probabilistic Logic Programming
Probabilistic logic programming is increasingly important in artificial
intelligence and related fields as a formalism to reason about uncertainty. It
generalises logic programming with the possibility of annotating clauses with
probabilities. This paper proposes a coalgebraic semantics on probabilistic
logic programming. Programs are modelled as coalgebras for a certain functor F,
and two semantics are given in terms of cofree coalgebras. First, the
F-coalgebra yields a semantics in terms of derivation trees. Second, by
embedding F into another type G, as cofree G-coalgebra we obtain a `possible
worlds' interpretation of programs, from which one may recover the usual
distribution semantics of probabilistic logic programming. Furthermore, we show
that a similar approach can be used to provide a coalgebraic semantics to
weighted logic programming