The authors have developed domain-independent techniques for reasoning and learning by
analogy, techniques that capture and apply problem-solving experience and that are useful …

This paper describes how apprenticeship learning techniques can be used to refine the
knowledge base of an expert system for heuristic classification problems. The described …

As knowledge-based systems are addressing increasingly complex domains, their roles are
shifting from classical expert systems to interactive assistants. To develop and maintain such …

This paper presents a decision support system (DSS) with inductive learning capability for
model management. Simulation is used as the primary environment for modeling …

The task of inductive learning from examples places constraints on the representation of
training instances and concepts. These constraints are different from, and often incompatible …

Several well-known factors contribute to interviewing problems: o Plausible lines of
reasoning can have little to do with actual problem-solving. o Academic (novice) knowledge …

Exploratory research contributes to the continued vitality of every discipline. The aim of
exploratory research is to identify new tasks-tasks that cannot be solved by existing …

This chapter presents DISCIPLE, a multistrategy, integrated learning system illustrating a
theory and a methodology for learning expert knowledge in the context of an imperfect …

This paper describes the first implementation of WebWatcher, a Learning Apprentice for the
World Wide Web. We also explore the possibility of extracting information from the structure …

The first problem discussed in this thesis is the logical problem of analogy, which, given a
formal definition of analogical inference, asks under what conditions such inferences may be …