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By Gary F. Marcus

An try and combine theories approximately how the brain works, person who says that the brain is a computer-like manipulator of symbols, and one other that claims that the brain is a big community of neurons operating jointly in parallel.

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By Gary F. Marcus

An try and combine theories approximately how the brain works, person who says that the brain is a computer-like manipulator of symbols, and one other that claims that the brain is a big community of neurons operating jointly in parallel.

Show description

Read or Download Algebraic Mind: Integrating Connectionism and Cognitive Science PDF

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Extra resources for Algebraic Mind: Integrating Connectionism and Cognitive Science

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227) seems to suggest this when he writes An individual’s overall-theory-of-the-world, we might venture, is not a large collection or a long list of stored symbolic items. Rather, it is a specific point in that individual’s synaptic weight space. It is a configuration of the connection weights, a configuration that partitions the system’s activation-vector space(s) into useful divisions and subdivisions relative to the inputs typically fed to the system. Book titles like Connections and Symbols (Pinker & Mehler, 1988) seem to further this impression.

Unbeknownst to the subjects, the feedback (in the one or two designated locations in which it was supplied) was secretly altered. This altered feedback caused subjects to alter their pointing behavior, but rather than compensating equally across the motor space, subjects compensated for the altered visual feedback most strongly in the locations at which they have received feedback. In other words, rather than transferring across the board, the degree to which subjects transferred declined rapidly as a function of the distance from the locations on which they were trained.

Hinton’s tests of the model were always within the training space—tests of whether the model could infer some fact about a family member about which many facts were already known. ) Similarly, Elman’s sentence-prediction model seems to be aimed squarely at cases in which humans can freely generalize—at accounting for how we acquire syntactic relationships between categories. To illustrate one way in which training independence would undermine the sentence-prediction model, in Marcus (1998c) I reported a series of simulations in which I trained the sentence-prediction model on sentences such as a rose is a rose, a lily is a lily, and a tulip is a tulip.

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