Stratified Knowledge Bases as Interpretable Probabilistic Models (Extended Abstract)

18 Nov 2016 Ondrej Kuzelka Jesse Davis Steven Schockaert

In this paper, we advocate the use of stratified logical theories for representing probabilistic models. We argue that such encodings can be more interpretable than those obtained in existing frameworks such as Markov logic networks... (read more)

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