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- W2183408553 abstract "This paper starts with an exposition of a new connectionist model. The model genemlizes more classical fully connected symrr:tetric networks. One of its main characteristics is that the state of a unit is characterized by a vector of amplitudes rather than by a single scalar . . activation value. The rules that express the evolution of the amplitudes of a particular unit are expressed. in terms of the amplitudes of the other units. The chance to observe a par ticular unit as being active in a particular frequency, however, is proportional with the square of the corresponding amplitude. Because of this as well as some other parallels with quantum theory, the model has been called QNET. QNET operates in different frequencies at once, and the operations in different frequencies interact with each other in a way that is desimble from a cognitive point of view. For instance, when confronted with a problem, QNET can find different solutions in differen~ frequencies. When different solutions are found, this often indicates that more classical networks fail to find a solution at all, since they then converge to a spurious mixture of solutions. We go on to consider how this type of network can be combined with genetic algorithms. We point out that a combination· of both methods leads to a technique that integrates the benefits of genetic algorithms with the ones of neural networks." @default.
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- W2183408553 date "1996-01-02" @default.
- W2183408553 modified "2023-10-16" @default.
- W2183408553 title "The Connectionist Model QNET and its Combination with Genetic Algorithms." @default.
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- W2183408553 doi "https://doi.org/10.21825/philosophica.82343" @default.
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