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Annual Conference on Artificial Intelligence

KI 2008: KI 2008: Advances in Artificial Intelligence pp 193–200Cite as

Partial Symbolic Pattern Databases for Optimal Sequential Planning

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5243))

Abstract

This paper investigates symbolic heuristic search with BDDs for solving domain-independent action planning problems cost-optimally. By distributing the impact of operators that take part in several abstractions, multiple partial symbolic pattern databases are added for an admissible heuristic, even if the selected patterns are not disjoint. As a trade-off between symbolic bidirectional and heuristic search with BDDs on rather small pattern sets, partial symbolic pattern databases are applied.

Thanks to DFG for support in the projects ED 74/3 and 74/2.

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Authors and Affiliations

  1. Faculty of Computer Science TU Dortmund, Germany

    Stefan Edelkamp & Peter Kissmann

Authors
  1. Stefan Edelkamp
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  2. Peter Kissmann
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Andreas R. Dengel Karsten Berns Thomas M. Breuel Frank Bomarius Thomas R. Roth-Berghofer

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Edelkamp, S., Kissmann, P. (2008). Partial Symbolic Pattern Databases for Optimal Sequential Planning. In: Dengel, A.R., Berns, K., Breuel, T.M., Bomarius, F., Roth-Berghofer, T.R. (eds) KI 2008: Advances in Artificial Intelligence. KI 2008. Lecture Notes in Computer Science(), vol 5243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85845-4_24

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  • DOI: https://doi.org/10.1007/978-3-540-85845-4_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85844-7

  • Online ISBN: 978-3-540-85845-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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