Affiliations: Departamento de Física e Matemática, R. Dom
Manoel de Medeiros, s/n, 52171-030, Recife (PE), Brazil. E-mail:
[email protected] | ICMC, Universidade de São Paulo at São Carlos,
Caixa Postal 668, 13560-970, São Carlos, SP, Brazil. E-mail:
[email protected] | Centro de Informática, UFPE, Av.Professor Luis
Freire, s/n, 50740-540, Recife, PE, Brazil. E-mail: [email protected]
Note: [] Corresponding author
Abstract: A novel way to simulate Turing Machines (TMs) by Artificial Neural
Networks (ANNs) is proposed. We claim that the proposed simulation is in
agreement with the correct interpretation of Turing's analysis of computation;
compatible with the current approaches to analyze cognition as an interactive
agent-environment process; and physically realizable since it does not use
connection weights with unbounded precision. A full description of an
implementation of a universal TM into a recurrent sigmoid ANN focusing on the
TM finite state control is given, leaving the tape, an infinite resource, as an
external non-intrinsic feature. Also, motivated by the results on the limit of
what can actually be computed by ANNs when noise is taken into account, we
introduce the notion of Definite Turing Machine and investigate some of its
properties.
