CP-logic theory inference with contextual variable elimination and comparison to BDD based inference methods

Authors:
Wannes Meert;Jan Struyf;Hendrik Blockeel
Affiliations:
Dept. of Computer Science, Katholieke Universiteit Leuven, Belgium;Dept. of Computer Science, Katholieke Universiteit Leuven, Belgium;Dept. of Computer Science, Katholieke Universiteit Leuven, Belgium
Venue:
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Year:
2009

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Abstract

There is a growing interest in languages that combine probabilistic models with logic to represent complex domains involving uncertainty. Causal probabilistic logic (CP-logic), which has been designed to model causal processes, is such a probabilistic logic language. This paper investigates inference algorithms for CP-logic; these are crucial for developing learning algorithms. It proposes a new CP-logic inference method based on contextual variable elimination and compares this method to variable elimination and to methods based on binary decision diagrams.