on Architectures for Integrating Neural and Symbolic Processing ) Combining
نویسنده
چکیده
This paper describes Rapture | a system for revising probabilistic knowledge bases that combines connectionist and symbolic learning methods. Rapture uses a modi ed version of backpropagation to re ne the certainty factors of a probabilistic rule base and it uses ID3's information-gain heuristic to add new rules. Results on re ning three actual expert knowledge bases demonstrate that this combined approach generally performs better than previous methods.
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