NEITHER is a propositional theory refinement system that will modify a incomplete or incorrect rule base so as to make it consistent with a set of input training examples. NEITHER has been extended to revise both Horn clauses and M-of-N rules. An iterative greedy method is used to efficiently compute repairs.
NEITHER has also been used as part of separate system, ASSERT, which performs student modeling. ASSERT (Acquiring Stereotypical Student Errors using Refinement of Theories) is an intelligent tutoring system which inputs a knowledge base describing a domain and a set of student errors on that domain and outputs a tutoring program tailored to fit student needs. Student behavior on the domain is modeled by collecting any refinements to the knowledge base (made by NEITHER) that were necessary to account for the student's behavior. These models are then used to generated feedback which should help raise student performance on that domain. More information can be found here.