Flexibility and Efficiency in a Computer Program for Designing Circuits
Flexibility and Efficiency in a Computer Program for Designing Circuits
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
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We believe that the capacity to recover intelligently from intermediate failures and to learn from these failures is an essential ingredient of attempting to solve complex real-world problems. Intelligent failure recovery requires the problem-solver not only to diagnose the causes of its failures, but also to circumscribe carefully the propagation of recovery updating. Learning from failures requires that the problem-solver remember the conditions of its failures in such a way that it will not recreate these conditions. In this paper, we describe methods providing such capabilities. We have implemented and experimented with these methods in a rule-based system used for designing complex assemblies such as electromechanical equipment.