BLOG: probabilistic models with unknown objects

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.

Publication
IJCAI'05: Proceedings of the 19th international joint conference on Artificial intelligence
David Sontag
David Sontag
Associate Professor of EECS

My research focuses on advancing machine learning and artificial intelligence, and using these to transform health care.

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