Towards Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm

Abstract

The lifted dynamic junction tree algorithm (LDJT) answers filtering and prediction queries efficiently for probabilistic relational temporal models by building and then reusing a first-order cluster representation of a knowledge base for multiple queries and time steps. Unfortunately, a non-ideal elimination order can lead to unnecessary groundings.
Original languageEnglish
Title of host publicationKI 2018: Advances in Artificial Intelligence
EditorsFrank Trollmann, Anni-Yasmin Turhan
Number of pages8
Volume11117
Place of PublicationCham
PublisherSpringer International Publishing
Publication date30.08.2018
Pages38-45
ISBN (Print)978-3-030-00110-0
ISBN (Electronic)978-3-030-00111-7
DOIs
Publication statusPublished - 30.08.2018
Event41st German Conference on Artificial Intelligence
- Berlin, Germany
Duration: 24.09.201828.09.2018
Conference number: 218679

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