Bucket elimination: a unifying framework for probabilistic inference
Proceedings of the NATO Advanced Study Institute on Learning in graphical models
On some tractable classes in deduction and abduction
Artificial Intelligence
Theorem Proving Based on the Extension Rule
Journal of Automated Reasoning
A survey on knowledge compilation
AI Communications
An analysis of approximate knowledge compilation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Knowledge compilation using theory prime implicates
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A perspective on knowledge compilation
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Approximate knowledge compilation: the first order case
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Compilation for critically constrained knowledge bases
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Prime Implicates and Reduced Implicate Tries
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Counting models using extension rules
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Reduced implicate/implicant tries
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Efficient query processing with compiled knowledge bases
TABLEAUX'05 Proceedings of the 14th international conference on Automated Reasoning with Analytic Tableaux and Related Methods
Duality in knowledge compilation techniques
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
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In this paper, we define a new class of tractable theories: EPCCL theories. Using EPCCL theories as a target language, we propose a new method for knowledge compilation. It is different from existing approaches in that both the compilation and the querying are based on the extension rule, a newly introduced inference rule. With our compilation method, arbitrary queries about the compiled knowledge base can be answered in linear time in the size of the compiled knowledge base. For some theories, the compilation can be done very efficiently, and the size of the compiled theory is small. Furthermore, our method suggests a new family of knowledge compilation methods.