This paper addresses the problem of learning the best approximation of a concept from examples, when the concept cannot be expressed in the learner's representation language. It presents a method that determines the version space of the best approximations and demonstrates that for any given approximation of the target concept there is a better approximation in this version space. The method does not depend on the order of examples and has an almost monotonic convergence. This method was

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... ed for the Disciple learning agent that can be taught by a subject matter expert how to perform complex problem solving tasks.