 Joohyung Lee and Yi Wang (Lee and Wang 2016) take a somewhat different approach, using the log-linear models of Markov Logic (Richardson and Domingos 2006), which they argue is a natural way to add probabilistic information to stable semantics for logic programming languages. A Markov Logic network is a way of finding the probability distribution to a Markov chain that is stationary, i.e., stable with respect to updating. Their approach incorporates the ProbLog model of Fierens et al. 2015 as a special case.