Language Learning in Massively-Parallel Networks
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Massively-parallel connectionist networks have traditionally been applied to constraint-satisfaction in early visual processing (Ballard, Hinton & Sejnowski, 1983), but are now being applied to problems ranging from the TravelingSalesman Problem to language acquisition (Rumelhart & MeClelland, 1986). In these networks, knowledge is represented by the distributed pat tern of activity in a large number of relatively simple neuron-like processing units, and computat ion is performed in parallel by the use of connections between the units.
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