# Dedicated Tabling for a Probabilistic Setting

@inproceedings{Mantadelis2010DedicatedTF, title={Dedicated Tabling for a Probabilistic Setting}, author={Theofrastos Mantadelis and Gerda Janssens}, booktitle={ICLP}, year={2010} }

ProbLog is a probabilistic framework that extends Prolog with probabilistic facts. To compute the probability of a query, the complete SLD proof tree of the query is collected as a sum of products. ProbLog applies advanced techniques to make this feasible and to assess the correct probability. Tabling is a well-known technique to avoid repeated subcomputations and to terminate loops. We investigate how tabling can be used in ProbLog. The challenge is that we have to reconcile tabling with the…

## 30 Citations

Nesting Probabilistic Inference

- Computer ScienceArXiv
- 2011

In order to support nested probabilistic inference in ProbLog, the notion of a parametrised ProbLog engine is proposed and several extensions of ProbLog such as meta-calls, negation, and answers of probabilism goals are realised.

Using Iterative Deepening for Probabilistic Logic Inference

- Computer SciencePADL
- 2017

An iterative deepening algorithm is presented which handles cycles and produces solutions to problems that previously ProbLog was not able to solve and is able to get the exact result for the same or one lower scaling factor.

The Most Probable Explanation for Probabilistic Logic Programs with Annotated Disjunctions

- Computer ScienceILP
- 2014

This work proposes a new encoding of annotated disjunctions which allows correct MARG and MPE and explores from both theoretical and experimental perspective the trade-off between the encoding suitable only for MARG inference and the newly proposed general approach.

Tabling for infinite probability computation

- Computer ScienceICLP
- 2012

This paper uses PRISM, a logic-based probabilistic modeling language with a tabling mechanism, to generalize prefix probability computation for PCFGs to Probabilistic logic programs, and opens a way to logic- based probabilism modeling of cyclic dependencies.

Inference in Probabilistic Logic Programs using Weighted CNF's

- Computer ScienceUAI
- 2011

This paper develops efficient inference algorithms for classical probabilistic inference tasks such as MAP and computing marginals based on a conversion of the Probabilistic logic program and the query and evidence to a weighted CNF formula.

Infinite probability computation by cyclic explanation graphs

- Computer ScienceTheory and Practice of Logic Programming
- 2013

The general approach to prefix probability computation through tabling not only allows to deal with non-probabilistic context-free grammars such as probabilistic left-corner Grammars but has applications such as plan recognition and Probabilistic model checking and makes it possible to compute probability for probabilism models describing cyclic relations.

Compacting Boolean Formulae for Inference in Probabilistic Logic Programming

- Computer ScienceLPNMR
- 2015

This work identifies 7 Boolean subformulae patterns that can be used to re-write Boolean formulae and implements an algorithm with polynomial complexity which detects and compacts 6 of these patterns, improving knowledge compilation and consecutively the overall inference performance.

Well–definedness and efficient inference for probabilistic logic programming under the distribution semantics

- Computer ScienceTheory and Practice of Logic Programming
- 2012

This paper presents the algorithm “Probabilistic Inference with Tabling and Answer subsumption” (PITA) that computes the probability of queries by transforming a probabilistic program into a normal program and then applying SLG resolution with answer subsumption.

ProbLog2: From probabilistic programming to statistical relational learning

- Computer ScienceNIPS 2012
- 2012

This work argues that the main mechanism behind ProbLog2 is a conversion of the given program to a weighted Boolean formula that can be applied with certain restrictions to other probabilistic programming languages such as Church and Figaro.

aspmc: An Algebraic Answer Set Counter

- Computer ScienceICLP Workshops
- 2021

We report about aspmc, which is the working prototype implementation of recent advances in Algebraic Answer Set Counting (AASC). AASC refers to counting the answer sets of a normal answer set program…

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