Efficient inference method for computing an optimal solution in predicate-logic hypothetical reasoning

Hypothetical reasoning, which is one type of abductive reasoning, is an important framework in the development of advanced knowledge-based systems. One problem with hypothetical reasoning is its slow inference speed, which is due to its nonmonotonic inference nature. A fast hypothetical reasoning system with predicate Horn clause expressions has been developed to overcome this problem. However, when the constraints for hypotheses are not strong, the number of hypotheses to be synthetized becomes too large to calculate. The paper presents an efficient hypothetical reasoning method combining best-first search, beam search and branch-and-bound search strategies for computing the optimal solution, which is the most desirable solution in many cases. The effectiveness of this method is shown experimentally using fault-diagnosis problems in logic circuits.