Abstract
Lifted algorithms use representatives for groups of indistinguishable objects to efficiently perform inference. Standard lifted algorithms like first-order variable elimination or first-order knowledge compilation, compute answers to marginal queries of single random variables or events in a lifted way using representatives. But, queries containing a set of indistinguishable random variables may lead to groundings, something that lifting tries to avoid. This paper presents parameterised queries as a means to avoid groundings, applying the lifting idea to queries. Parameterised queries enable lifted algorithms to compute answers faster, while compactly representing queries and answers.
| Original language | English |
|---|---|
| Title of host publication | Frontiers in Artificial Intelligence and Applications |
| Editors | Giuseppe De Giacomo , Alejandro Catala , Bistra Dilkina , Michela Milano , Senén Barro , Alberto Bugarín , Jérôme Lang |
| Number of pages | 22 |
| Volume | 325 |
| Publisher | IOS Press |
| Publication date | 24.08.2020 |
| Pages | 2891 - 2892 |
| ISBN (Print) | 978-1-64368-100-9 |
| ISBN (Electronic) | 978-1-64368-101-6 |
| DOIs | |
| Publication status | Published - 24.08.2020 |
| Event | 24th European Conference on Artificial Intelligence - Online Streaming , Santiago de Compostela, Spain Duration: 29.08.2020 → 08.09.2020 Conference number: 162625 |
Research Areas and Centers
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
- Research Area: Intelligent Systems
