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Blog: Probabilistic models with unknown objects (2005)

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by Brian Milch , Bhaskara Marthi , Stuart Russell , David Sontag , Daniel L. Ong , Andrey Kolobov
Venue:In IJCAI
Citations:99 - 10 self
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DatumValueSource
TITLE Blog: Probabilistic models with unknown objects INFERENCE
AUTHOR NAME Brian Milch SVM HeaderParse 0.2
AUTHOR AFFIL Computer Science Division; University of California SVM HeaderParse 0.2
AUTHOR ADDR Berkeley, CA 94720-1776 SVM HeaderParse 0.2
AUTHOR NAME Bhaskara Marthi SVM HeaderParse 0.2
AUTHOR AFFIL Computer Science Division; University of California SVM HeaderParse 0.2
AUTHOR ADDR Berkeley, CA 94720-1776 SVM HeaderParse 0.2
AUTHOR NAME Stuart Russell SVM HeaderParse 0.2
AUTHOR AFFIL Computer Science Division; University of California SVM HeaderParse 0.2
AUTHOR ADDR Berkeley, CA 94720-1776 SVM HeaderParse 0.2
AUTHOR NAME David Sontag SVM HeaderParse 0.2
AUTHOR AFFIL Computer Science Division; University of California SVM HeaderParse 0.2
AUTHOR ADDR Berkeley, CA 94720-1776 SVM HeaderParse 0.2
AUTHOR NAME Daniel L. Ong SVM HeaderParse 0.2
AUTHOR AFFIL Computer Science Division; University of California SVM HeaderParse 0.2
AUTHOR ADDR Berkeley, CA 94720-1776 SVM HeaderParse 0.2
AUTHOR NAME Andrey Kolobov SVM HeaderParse 0.2
AUTHOR AFFIL Computer Science Division; University of California SVM HeaderParse 0.2
AUTHOR ADDR Berkeley, CA 94720-1776 SVM HeaderParse 0.2
ABSTRACT This paper introduces and illustrates BLOG, a formal language for defining probability models over worlds with unknown objects and identity uncertainty. BLOG unifies and extends several existing approaches. Subject to certain acyclicity constraints, every BLOG model specifies a unique probability distribution over first-order model structures that can contain varying and unbounded numbers of objects. Furthermore, complete inference algorithms exist for a large fragment of the language. We also introduce a probabilistic form of Skolemization for handling evidence. 1 SVM HeaderParse 0.2
YEAR 2005 INFERENCE
VENUE In IJCAI INFERENCE
VENUE TYPE CONFERENCE INFERENCE
PAGES 1352--1359 INFERENCE
CITATIONS 21 found ParsCit 1.0
The National Science Foundation
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