2010
DOI: 10.1007/978-3-642-15675-5_23
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Abstract: This section analyzes the worst case complexity of our preprocessing algorithms. We use N to denote the number of proofs or conjunctions and M to denote the number of probabilistic facts or Boolean variables. By our experience, N >> M usually holds for typical ProbLog programs.

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Cited by 4 publications
(6 citation statements)
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“…2. Boolean formula preprocessing takes the compact representation of the possible worlds in order to perform cycle handling [10] and optimize it as a Boolean formula [11]. 3.…”
Section: Problog and The Distribution Semanticsmentioning
confidence: 99%
See 2 more Smart Citations
“…2. Boolean formula preprocessing takes the compact representation of the possible worlds in order to perform cycle handling [10] and optimize it as a Boolean formula [11]. 3.…”
Section: Problog and The Distribution Semanticsmentioning
confidence: 99%
“…ProbLog supports several different preprocessing methods. In this work, we used the Recursive Node Merging preprocessing method [11]. The preprocessing procedure is responsible for writing the AND-OR graph as a depth breadth trie.…”
Section: Iterative Deepening Cycle Handlingmentioning
confidence: 99%
See 1 more Smart Citation
“…We focus on 4 particular ProbLog pipelines, based on two mainstream ProbLog implementations -MetaProbLog [17] and ProbLog2 [8]. These inference pipelines differ with respect to (a) representation of the Ground LP and the Boolean formulae: ProbLog2 uses AND-OR graphs and CNF DIMACS, while MetaProbLog uses Nested Tries [15] and BDD scripts [14]; (b) ways of preprocessing the Boolean formulae: ProbLog2 uses Boolean subformulae repetition detection and MetaProbLog uses the recursive node merging method presented in [18]; and (c) in the knowledge compilation method: ProbLog2 uses the sd-DNNF compiler c2d [5] and MetaProbLog uses the SimpleCUDD [14] compiler for ROBDDs. The 4 pipelines we use for our experiments are listed in Table 2.…”
Section: Compacting Problog Programsmentioning
confidence: 99%
“…Choosing the optimal variable ordering is NP-hard. A comprehensive review of different construction techniques is presented by Mantadelis et al [29]. Discussion: All the approaches mentioned above present significant limitations in presence of correlations and local structure.…”
Section: Pr(w)mentioning
confidence: 99%