Neural Symbolic Computation
Mostrando 1-3 de 3 artigos, teses e dissertações.
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1. The grand challenges and myths of neural-symbolic computation
Publicado em: 2011
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2. Symbolic processing in neural networks
In this paper we show that programming languages can be translated into recurrent (analog, rational weighted) neural nets. Implementation of programming languages in neural nets turns to be not only theoretical exciting, but has also some practical implications in the recent efforts to merge symbolic and sub symbolic computation. To be of some use, it should
Journal of the Brazilian Computer Society. Publicado em: 2003-04
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3. A dynamical systems perspective on the relationship between symbolic and non-symbolic computation
It has been claimed that connectionist (artificial neural network) models of language processing, which do not appear to employ “rules”, are doing something different in kind from classical symbol processing models, which treat “rules” as atoms (e.g., McClelland and Patterson in Trends Cogn Sci 6(11):465–472, 2002). This claim is hard to assess in
Springer Netherlands.