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<p>The authors present a system, called SAFE (strategy acquisition from experience), which incorporates novel methods for discovering domain-dependent problem-solving heuristics. SAFE is implemented as a sorting system whose sorting strategies are represented as production rules. SAFE initially uses the insertion sort strategy to solve problems. After solving each given problem. SAFE learns symbolic rules from the solution path which is obtained by applying the existing heuristic information. By one or several processes of learning. SAFE is able to obtain the heuristics to sort new problems with minimum exchanges of elements. The notion of shortcut, an effective inductive learning bias for reducing the hypothesis space to be searched during learning, is introduced.</p>
symbolic rule learning; elements exchange; SAFE; strategy acquisition from experience; domain-dependent problem-solving heuristics; sorting system; production rules; insertion sort; solution path; heuristic information; shortcut; inductive learning bias; hypothesis space; heuristic programming; inference mechanisms; knowledge acquisition; learning systems; problem solving; sorting

W. Wang and J. Chen, "Learning by Discovering Problem Solving Heuristics Through Experience," in IEEE Transactions on Knowledge & Data Engineering, vol. 3, no. , pp. 415-420, 1991.
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