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BLOG: Probabilistic Models with Unknown Objects (2006)

Abstract
We introduce BLOG, a formal language for defining probability models with unknown objects and identity uncertainty. A BLOG model describes a generative process in which some steps add objects to the world, and others determine attributes and relations on these objects. Subject to certain acyclicity constraints, a BLOG model specifies a unique probability distribution over first-order model structures that can contain varying and unbounded numbers of objects. Furthermore, inference algorithms exist for a large class of BLOG models.. @InProceedings{milch_et_al:DSP:2006:416, author = {Brian Milch and Bhaskara Marthi and Stuart Russell and David Sontag and Daniel L. Ong and Andrey Kolobov}, title = {BLOG: Probabilistic Models with Unknown Objects}, booktitle = {Probabilistic, Logical and Relational Learning - Towards a Synthesis}, year = {2006}, editor = {Luc De Raedt and Thomas Dietterich and Lise Getoor and Stephen H. Muggleton}, number = {05051}, series = {Dagstuhl Seminar Proceedings}, ISSN = {1862-4405}, publisher = {Internationales Begegnungs- und Forschungszentrum f{"u}r Informatik (IBFI), Schloss Dagstuhl, Germany}, address = {Dagstuhl, Germany}, URL = {http://drops.dagstuhl.de/opus/volltexte/2006/416}, annote = {Keywords: Knowledge representation, probability, first-order logic, identity uncertainty, unknown objects} }

Publication details
Download http://drops.dagstuhl.de/opus/volltexte/2006/416/
Publisher Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Dagstuhl Seminar Proceedings. 05051 - Probabilistic, Logical and Relational Learning - Towards a Synthesis
Repository DROPS - Dagstuhl Research Online Publication Server ()
Keywords Knowledge representation, probability, first-order logic, identity uncertainty, unknown objects, Data processing Computer science, General Literature
Type InProceedings
Language eng