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Revisão de Teorias Probabilísticas de Primeira-Ordem

Aline PaesKate RevoredoGerson ZaveruchaVitor Santos Costa

There has been a lot of work in the integration of probabilistic reasoning with first order logic representations. Learning algorithms for these models have been developed and they all considered modifications in the entire structure. Previously Revoredo and Zaverucha argued that when the theory is approximately correct the use of techniques from theory revision to just modify the structure in places that failed in logically covering the examples can be a more adequate choice. In the present paper, we extend this revision system showing the necessity of using specialization operators, even though there are no negative examples, and compare the experimental results of a theory modified only in places misclassified with one that was modified in the entire structure.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2005/065.pdf

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