Abstract
Standard approaches for inference in probabilistic formalisms with first-order constructs include lifted variable elimination (LVE) for single queries as well as first-order knowledge compilation (FOKC) based on weighted model counting. To handle multiple queries efficiently, the lifted junction tree algorithm (LJT) uses a first-order cluster representation of a model and LVE as a subroutine in its computations. For certain inputs, the implementation of LVE and, as a result, LJT ground parts of a model where FOKC runs without groundings. The purpose of this paper is to prepare LJT as a backbone for lifted query answering and to use any exact inference algorithm as subroutine. Fusing LJT and FOKC, by setting FOKC as a subroutine, allows us to compute answers faster than FOKC alone and LJT with LVE for certain inputs.
| Original language | English |
|---|---|
| Title of host publication | KI 2018: Advances in Artificial Intelligence |
| Editors | Frank Trollmann, Anni-Yasmin Turhan |
| Number of pages | 14 |
| Volume | 11117 |
| Place of Publication | Cham |
| Publisher | Springer International Publishing |
| Publication date | 30.08.2018 |
| Pages | 24-37 |
| ISBN (Print) | 978-3-030-00110-0 |
| ISBN (Electronic) | 978-3-030-00111-7 |
| DOIs | |
| Publication status | Published - 30.08.2018 |
| Event | 41st German Conference on Artificial Intelligence - Berlin, Germany Duration: 24.09.2018 → 28.09.2018 Conference number: 218679 |
Research Areas and Centers
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
- Research Area: Intelligent Systems
DFG Research Classification Scheme
- 4.43-01 Theoretical Computer Science
