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Encoding Domain and Control Knowledge for Propositional Planning

  • Henry Kautz
  • Bart Selman
Chapter
Part of the The Springer International Series in Engineering and Computer Science book series (SECS, volume 597)

Abstract

Propositional satisfiability checking is a powerful approach to domain-independent planning. In nearly all practical applications, however, there exists an abundance of domain-specific knowledge that can be used to improve the performance of a planning system. This knowledge is traditionally encoded as procedures or rules that are tied to the details of the planning engine. We present a way to encode domain knowledge in a purely declarative, algorithm independent manner. We demonstrate that the same heuristic knowledge can be used by completely different search engines, one systematic, the other using greedy local search. This approach enhances the power of planning as satisfiability: solution times for some problems are reduced from days to seconds.

Keywords

SATPLAN BlackBox planning satisfiability domain knowledge 

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Henry Kautz
    • 1
  • Bart Selman
    • 2
  1. 1.University of WashingtonSeattleUSA
  2. 2.Cornell UniversityIthacaUSA

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