### Abstract

Inference in probabilistic logic languages such as ProbLog, an extension of Prolog with probabilistic facts, is often based on a reduc- tion to a propositional formula in DNF. Calculating the probability of such a formula involves the disjoint-sum-problem, which is computation- ally hard. In this work we introduce a new approximation method for ProbLog inference which exploits the DNF to focus sampling. While this DNF sampling technique has been applied to a variety of tasks before, to the best of our knowledge it has not been used for inference in probabilis- tic logic systems. The paper also presents an experimental comparison with another sampling based inference method previously introduced for ProbLog.

Original language | English |
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Number of pages | 1 |

Publication status | Published - 2010 |

Externally published | Yes |

Event | 26th International Conference on Logic Programming, ICLP 2010 - Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in Programming Environments - CICLOPS-WLPE 2010 - Edinburgh, Scotland, United Kingdom Duration: 15 Jul 2010 → 15 Jul 2010 |

### Conference

Conference | 26th International Conference on Logic Programming, ICLP 2010 - Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in Programming Environments - CICLOPS-WLPE 2010 |
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Country | United Kingdom |

City | Edinburgh, Scotland |

Period | 15/07/10 → 15/07/10 |

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## Cite this

*DNF sampling for ProbLog inference*. Paper presented at 26th International Conference on Logic Programming, ICLP 2010 - Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in Programming Environments - CICLOPS-WLPE 2010, Edinburgh, Scotland, United Kingdom.