1999 Volume 14 Issue 6 Pages 1100-1107
For propositional-version hypothetical reasoning (or abduction), particularly for its cost-based one, some efficient methods have been developed, which achieve polynomial-time reasoning with respect to problem size to compute a near-optimal solution. However, for predicate-version hypothetical reasoning that allows rich and compact knowledge representation, it seems difficult to find such a method with polynomial-order efficiency as long as we stick to symbolic manipulation. As a result, there has been no good efficient method so far in predicate-logic domain. A naive approach for efficient predicate-version hypothetical reasoning is to transform predicate knowledge in to propositional knowledge, and ten to apply and efficient method in propositional domain. This can be accomplished by a transformation in the Herbrand universe; however, this is impractical since a vast number of propositional clauses will be produced. We tried to use a deductive database technique, namely, QSQR method, to extract a knowledge portion being related to the proof of a given goal of hypothetical reasoning, and then to transform only this portion into propositional knowledge. Nevertheless, it can not improve reasoning efficiency enough because a considerable computational time is required for the transformation into propositional knowledge by the QSQR method, and the number of the resulting propositional clauses is still large. In this paper, we propose a knowledge reformation scheme for predicate rules such that the transformation into propositional rules is efficient and the number of the resulting propositional rules is small. This knowledge reformation is based on unfolding/folding processes for predicate rules. Although its applicable range is still limited, it is shown experimentally that, by introducing this knowledge reformation, a large amount of efficiency improvement is achieved for predicate-version cost-based hypothetical reasoning.
