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• W2465254145 abstract "We propose TP-compilation, a new inference technique for probabilistic logic programs that is based on forward reasoning. TP-compilation proceeds incrementally in that it interleaves the knowledge compilation step for weighted model counting with forward reasoning on the logic program. This leads to a novel anytime algorithm that provides hard bounds on the inferred probabilities. The main difference with existing inference techniques for probabilistic logic programs is that these are a sequence of isolated transformations. Typically, these transformations include conversion of the ground program into an equivalent propositional formula and compilation of this formula into a more tractable target representation for weighted model counting. An empirical evaluation shows that TP-compilation effectively handles larger instances of complex or cyclic real-world problems than current sequential approaches, both for exact and anytime approximate inference. Furthermore, we show that TP-compilation is conducive to inference in dynamic domains as it supports efficient updates to the compiled model." @default.
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• W2465254145 date "2016-11-01" @default.
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• W2465254145 title "<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML altimg=si1.gif overflow=scroll><mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=script>P</mml:mi></mml:mrow></mml:msub></mml:math>-Compilation for inference in probabilistic logic programs" @default.
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• W2465254145 doi "https://doi.org/10.1016/j.ijar.2016.06.009" @default.
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