Probabilistic logic programming for hybrid relational domains

  title={Probabilistic logic programming for hybrid relational domains},
  author={Davide Nitti and Tinne De Laet and Luc De Raedt},
  journal={Machine Learning},
We introduce a probabilistic language and an efficient inference algorithm based on distributional clauses for static and dynamic inference in hybrid relational domains. Static inference is based on sampling, where the samples represent (partial) worlds (with discrete and continuous variables). Furthermore, we use backward reasoning to determine which facts should be included in the partial worlds. For filtering in dynamic models we combine the static inference algorithm with particle filters… CONTINUE READING