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Abstraction has proven to be a powerful tool for controlling the combinatorics of a problemsolving search. It is also of critical importance for learning systems. In this article we present, and evaluate experimentally, a general abstraction method -- impasse-driven abstraction - which is able to provide necessary assistance to both problem solving and learning. It reduces the amount of time required to solve problems, and the time required to learn new rules. In addition, it results in the acquisition of rules that are more general than would have otherwise been learned.