Semantic Selection for Resolution in Clause Graphs

  • Authors:

  • Seungyeob Choi;Manfred Kerber

  • Affiliations:

  • -;-

  • Venue:
  • AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
  • Year:
  • 2002

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Abstract

In this contribution we present a variant of a resolution theorem prover which selects resolution steps based on the proportion of models a newly generated clause satisfies compared to all models given in a reference class. This reference class is generated from a subset of the initial clause set. Since the empty clause does not satisfy any models, preference is given to such clauses which satisfy few models only. Because computing the number of models is computationally expensive on the one hand, but will remain almost unchanged after the application of one single resolution step on the other hand, we adapt Kowalski's connection graph method to store the number of models at each link.