Detection of semantically incorrect rules in knowledge-based systems

摘要

A novel approach that applies the technique of back propagation to the recognition of semantically incorrect rules is presented. When the rule strengths of most rules are semantically correct, semantically incorrect rules can be recognized if their strengths are weakened or change signs after training with correct samples. In each training cycle, the discrepancies in the belief values of goal hypotheses are propagated backwards, and the strengths of rules responsible for such discrepancies are modified appropriately. A function called consistent-shift is defined for measuring the shift of a rule strength in the direction that is consistent with the strength assigned before training, and this is a critical component of this technique. A formal analysis of this approach is provided. The viability of this technique has been demonstrated in a practical domain.