"Probabilistic Logic Learning" - Tutorial

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Intended Audience

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Probabilistic Logic Learning is a multi-disciplinary research area. Therefore, the tutorial is directed to a rather general audience such as machine learning, uncertainty in AI, statistical inference, inductive logic programming, multi-relational data mining etc. Basic knowledge of the three underlying constituents would be helpful, but is not prerequisite. The tutorial will be as self-content as possible. The main goal of the tutorial is to provide an introduction to and a survey of approaches to probabilistic logic learning that address the intersection of probabilistic logic learning. It should allow attendees to appreciate the differences and commonalities between the various approaches.