  We present plingo, an extension of the ASP system clingo with various
probabilistic reasoning modes. Plingo is centered upon LP^MLN, a probabilistic
extension of ASP based on a weight scheme from Markov Logic. This choice is
motivated by the fact that the core probabilistic reasoning modes can be mapped
onto optimization problems and that LP^MLN may serve as a middle-ground
formalism connecting to other probabilistic approaches. As a result, plingo
offers three alternative frontends, for LP^MLN, P-log, and ProbLog. The
corresponding input languages and reasoning modes are implemented by means of
clingo's multi-shot and theory solving capabilities. The core of plingo amounts
to a re-implementation of LP^MLN in terms of modern ASP technology, extended by
an approximation technique based on a new method for answer set enumeration in
the order of optimality. We evaluate plingo's performance empirically by
comparing it to other probabilistic systems.
