Concepts and Categorisation 2

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1. In the connectionist approach, what do weights determine?

  • How strongly an incoming signal will influence the activity of the next unit
  • Whether the output units are adjusted to give the correct information
  • How knowledge is represented in the distributed activity of many units
  • Difference between actual activity of each output unit and the correct activity
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2. Which process does not occur in learning?

  • Back-propagation repeats until the error signal is 1
  • Weights should be changed to allow the output signal to match the correct signal
  • Whether or not the output units are given you the correct information they are adjusted
  • Responding is modified to match the correct response

3. In the connectionist approach, what does the error signal determine?

  • How knowledge is represented in the distributed activity of many units
  • How strongly an incoming signal will influence the activity of the next unit
  • Difference between actual activity of each output unit and the correct activity
  • Whether the output units are adjusted to give the correct information

4. Semantic networks show a cognitive economy. What is this?

  • Lower-level items share properties of high-level items
  • Shared properties are only stored at higher-level nodes
  • Excepts are stored at lower nodes
  • How concepts and properties are associated in the mind

5. How is the exemplar approach different to the prototype approach?

  • Representation is not abstract
  • May work best for larger categories
  • Descriptions of broad examples
  • Cannot explain the typicality effect

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