Abstract
Second generation expert systems are able to combine heuristic reasoning based on rules, with deep reasoning based on a model of the problem domain. This solves a number of major problems of current expert systems, most importantly the problem of knowledge acquisition: second generation expert systems can learn new rules by examining the results of deep reasoning. The paper outlines the components of second generation expert systems and gives an example.
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