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- W2979173693 abstract "For a computational system to be intelligent, it should be able to perform, at least, basic deductions. Nonetheless, since deductions are, in some sense, equivalent to tautologies, it seems that they do not provide new information. In order to analyze this problem, the present article proposes a measure of the degree of semantic informativity of valid deductions. Concepts of coherency and relevancy, displayed in terms of insertions and deletions on databases, are used to define semantic informativity. In this way, the article shows that a solution to the problem about informativity of deductions provides a heuristic principle to improve the deductive power of computational systems." @default.
- W2979173693 created "2019-10-10" @default.
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- W2979173693 date "2016-01-01" @default.
- W2979173693 modified "2023-09-27" @default.
- W2979173693 title "Semantic Information and Artificial Intelligence" @default.
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- W2979173693 doi "https://doi.org/10.1007/978-3-319-26485-1_9" @default.
- W2979173693 hasPublicationYear "2016" @default.
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