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What does the mind learn? A comparison of human and machine learning representations
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Spicer, Jake and Sanborn, Adam N. (2019) What does the mind learn? A comparison of human and machine learning representations. Current Opinion in Neurobiology, 55 . pp. 97-102. doi:10.1016/j.conb.2019.02.004
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Official URL: https://doi.org/10.1016/j.conb.2019.02.004
Abstract
We present a brief review of modern machine learning techniques and their use in models of human mental representations, detailing three notable branches: spatial methods, logical methods and artificial neural networks. Each of these branches contain an extensive set of systems, and demonstrate accurate emulations of human learning of categories, concepts and language, despite substantial differences in operation. We suggest that continued applications will allow cognitive researchers the ability to model the complex real-world problems where machine learning has recently been successful, providing more complete behavioural descriptions. This will however also require careful consideration of appropriate algorithmic constraints alongside these methods in order to find a combination which captures both the strengths and weaknesses of human cognition.
| Item Type: | Journal Article | ||||||||
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| Divisions: | Faculty of Science > Psychology | ||||||||
| Journal or Publication Title: | Current Opinion in Neurobiology | ||||||||
| Publisher: | Elsevier Science BV | ||||||||
| ISSN: | 0959-4388 | ||||||||
| Official Date: | April 2019 | ||||||||
| Dates: |
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| Volume: | 55 | ||||||||
| Page Range: | pp. 97-102 | ||||||||
| DOI: | 10.1016/j.conb.2019.02.004 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
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