  First-order model counting emerged recently as a novel reasoning task, at the
core of efficient algorithms for probabilistic logics. We present a
Skolemization algorithm for model counting problems that eliminates existential
quantifiers from a first-order logic theory without changing its weighted model
count. For certain subsets of first-order logic, lifted model counters were
shown to run in time polynomial in the number of objects in the domain of
discourse, where propositional model counters require exponential time.
However, these guarantees apply only to Skolem normal form theories (i.e., no
existential quantifiers) as the presence of existential quantifiers reduces
lifted model counters to propositional ones. Since textbook Skolemization is
not sound for model counting, these restrictions precluded efficient model
counting for directed models, such as probabilistic logic programs, which rely
on existential quantification. Our Skolemization procedure extends the
applicability of first-order model counters to these representations. Moreover,
it simplifies the design of lifted model counting algorithms.
