BLOG: Probabilistic Models with Unknown Objects

Authors Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov



PDF
Thumbnail PDF

File

DagSemProc.05051.4.pdf
  • Filesize: 113 kB
  • 6 pages

Document Identifiers

Author Details

Brian Milch
Bhaskara Marthi
Stuart Russell
David Sontag
Daniel L. Ong
Andrey Kolobov

Cite AsGet BibTex

Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, and Andrey Kolobov. BLOG: Probabilistic Models with Unknown Objects. In Probabilistic, Logical and Relational Learning - Towards a Synthesis. Dagstuhl Seminar Proceedings, Volume 5051, pp. 1-6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)
https://doi.org/10.4230/DagSemProc.05051.4

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.
Keywords
  • Knowledge representation
  • probability
  • first-order logic
  • identity uncertainty
  • unknown objects

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail