Gries, OliverOliverGries2022-01-242022-01-242011-125th International Workshop, MIWAI 2011http://hdl.handle.net/11420/11541There is a growing interest in the logical representation of both probabilistic and deterministic dependencies. While Gibbs sampling is a widely-used method for estimating probabilities, it is known to give poor results in the presence of determinism. In this paper, we consider acyclic Horn logic, a small, but significant fragment of first-order logic and show that Markov chains constructed with Gibbs sampling remain ergodic with deterministic dependencies specified in this fragment. Thus, there is a new subclass of Gibbs sampling procedures known to approximate the correct probabilities and expected to be useful for lots of applications.enDeterministic DependenciesGibbs SamplingMarkov NetworksProbabilistic InferenceInformatikConference Paper10.1007/978-3-642-25725-4_37