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  Fast Probabilistic Planning Through Weighted Model Counting

Domshlak, C., & Hoffmann, J. (2006). Fast Probabilistic Planning Through Weighted Model Counting. In Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS 2006) (pp. 243-252). Menlo Park, USA: AAAI.

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 Creators:
Domshlak, Carmel, Author
Hoffmann, Jörg1, Author           
Long, Derek, Editor
Smith, Stephen F., Editor
Borrajo, Daniel, Editor
McCluskey, Lee, Editor
Affiliations:
1Programming Logics, MPI for Informatics, Max Planck Society, ou_40045              

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 Abstract: We present a new algorithm for probabilistic planning with no observability. Our algorithm, called Probabilistic-FF, extends the heuristic forward-search machinery of Conformant-FF to problems with probabilistic uncertainty about both the initial state and action effects. Specifically, Probabilistic-FF combines Conformant-FF's techniques with a powerful machinery for weighted model counting in (weighted) CNFs, serving to elegantly define both the search space and the heuristic function. Our evaluation of Probabilistic-FF on several probabilistic domains shows an unprecedented, several orders of magnitude improvement over previous results in this area.

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Language(s): eng - English
 Dates: 2007-04-242006
 Publication Status: Issued
 Pages: -
 Publishing info: Menlo Park, USA : AAAI
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 314650
Other: Local-ID: C1256104005ECAFC-3E95E26F349AEB6AC1257114003AA62D-DomshlakHoffmann2006
 Degree: -

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Title: Untitled Event
Place of Event: The English Lake District
Start-/End Date: 2006-06-06

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Title: Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS 2006)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Menlo Park, USA : AAAI
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 243 - 252 Identifier: ISBN: 978-1-57735-270-9