Since the late nineties there has been an increased interested in probabilistic logic learning, an area within AI that combines machine learning with logic-based knowledge representation and uncertainty reasoning. Several different formalisms for combining first-order logic with probability reasoning have been proposed, and it has been studied how models in these formalisms can be automatically learned from data.
CITATION STYLE
Blockeel, H. (2008). Exposing the Causal Structure of Processes by Learning CP-Logic Programs (pp. 2–2). https://doi.org/10.1007/978-3-540-89197-0_2
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