Reasoning with Probabilistic Logics
  The interest in the combination of probability with logics for modeling the
world has rapidly increased in the last few years. One of the most effective
approaches is the Distribution Semantics which was adopted by many logic
programming languages and in Descripion Logics. In this paper, we illustrate
the work we have done in this research field by presenting a probabilistic
semantics for description logics and reasoning and learning algorithms. In
particular, we present in detail the system TRILL P, which computes the
probability of queries w.r.t. probabilistic knowledge bases, which has been
implemented in Prolog. Note: An extended abstract / full version of a paper
accepted to be presented at the Doctoral Consortium of the 30th International
Conference on Logic Programming (ICLP 2014), July 19-22, Vienna, Austria
