Essentially, knowledge level modeling involves evaluating an agent's world and all possible states and with that information constructing a model that depicts the interrelations and pathways between the various states. With this model, various problem solving methods (i.e. prediction, classification, explanation, tutoring, qualitative reasoning, planning, etc.) can be viewed in a uniform fashion.
In , Menzies proposes a new knowledge level modeling approach, called KLB, which specifies that "a knowledge base should be divided into domain-specific facts and domain-independent abstract problem solving inference procedures." In his method, abductive reasoning is used to find assumptions which, when combined with theories, achieve the desired goals of the system.
For a good example of abductive reasoning, look at logical reasoning.
 T. Menzies. Applications of Abduction: Knowledge-Level Modeling. November 1996