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It is by now well recognized that a major impediment to developing knowledge-based systems is the knowledge-acquisition bottleneck: The task of building up a complete enough and correct enough knowledge base to provide high-level performance. This chapter proposes a new class of knowledge-based systems designed to address this knowledge-acquisition bottleneck by incorporating a learning component to acquire new knowledge through experience. In particular, we define learning apprentice systems as the class of interactive, knowledge-based consultants that directly assimilate new knowledge by observing and analyzing the problem-solving steps contributed by their users through their normal use of the system. This chapter describes a specific learning apprentice system, called LEAP, which is currently being developed in the domain of VLSI design. We also discuss design issues for learning …