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Selecting Knowledge for Category Learning
Abstract
We present a category learning experiment in which subjects faced the knowledge selection problem, i.e., they needed to use their observations to determine which prior knowledge would be useful for learning. The issue of putting prior knowledge into neural network models is reviewed, and we present a new model which addresses the knowledge selection problem. This model gives a good account of the experimental results.
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