A symbolic model of the nonconscious acquisition of information

Abstract

This article presents counter evidence against Smolensky's theory that human intuitive/nonconscious congnitive processes can only be accurately explained in terms of subsymbolic computations carried out in artificial neural networks. We present symbolic learning models of two well-studied, complicated cognitive tasks involving nonconscious acquisition of information: learning production rules and artificial finite state grammars. Our results demonstrate that intuitive learning does not imply subsymbolic computation, and that the already well-established, perceived correlation between “conscious” and “symbolic” on the one hand, and between “nonconscious” and “subsymbolic” on the other, does not exist.