ABSTRACT
This chapter examines the evolution of Artificial Intelligence (AI) work in planning, problem solving as it has evolved in the 1970s and 1980s. The development of case-based reasoning and explanation-based learning within AI in the 1980s was motivated by several sets of issues, including that of the organization of dynamic memory and the desire to overcome the limitations of rule-based systems—limitations that have become all too apparent after twenty years of experience. Sophisticated rule-based systems may consist of a number of modules, some of which elicit data from users, monitor the state of the rule base, or offer explanations by backtracking through the chain of rules used to reach a conclusion. Case-based reasoning can be interpreted as one such effort. If case-based reasoning is a truer model of human reasoning, then it should be easier to transfer knowledge from human experts to systems designed on the principles.
