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» An Effective QBF Solver for Planning Problems
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JSAT
2006
126views more  JSAT 2006»
13 years 5 months ago
Complexity Results for Quantified Boolean Formulae Based on Complete Propositional Languages
Several propositional fragments have been considered so far as target languages for knowledge compilation and used for improving computational tasks from major AI areas (like infe...
Sylvie Coste-Marquis, Daniel Le Berre, Florian Let...
AUSAI
2004
Springer
13 years 10 months ago
Embedding Memoization to the Semantic Tree Search for Deciding QBFs
Abstract. Quantified Boolean formulas (QBFs) play an important role in artificial intelligence subjects, specially in planning, knowledge representation and reasoning [20]. In th...
Mohammad GhasemZadeh, Volker Klotz, Christoph Mein...
AIPS
2000
13 years 6 months ago
Investigating the Effect of Relevance and Reachability Constraints on SAT Encodings of Planning
Currently, Graphplan and Blackbox, which converts Graphplan's plan graph into the satisfaction (SAT) problem, are two of the most successful planners. Since Graphplan gains i...
Minh Binh Do, Biplav Srivastava, Subbarao Kambhamp...
ICTAI
2002
IEEE
13 years 10 months ago
DSatz: A Directional SAT Solver for Planning
(Appears as a regular paper in the proceedings of IEEE International Conference on Tools with Artificial Intelligence (ICTAI), IEEE Computer Society, Washington D.C, Nov. 2002, p...
Mark Iwen, Amol Dattatraya Mali
ICCBR
2009
Springer
13 years 3 months ago
Constraint-Based Case-Based Planning Using Weighted MAX-SAT
Previous approaches to case-based planning often finds a similar plan case to a new planning problem to adapt to solve the new problem. However, in the case base, there may be some...
Hankui Zhuo, Qiang Yang, Lei Li