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Models of word reading: theory-building vs. data-fitting| old_uid | 3442 |
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| title | Models of word reading: theory-building vs. data-fitting |
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| start_date | 2007/11/13 |
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| schedule | 11h-12h |
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| online | no |
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| summary | I will discuss two (not the only) approaches to models of word reading: the distributed connectionist approach developed by myself, McClelland, Plaut and others, and the DRC approach developed by Coltheart and colleagues. The two approaches entail very different
goals and criteria for success. Our goal has been to explore a set of basic principles thought to underlie many aspects of cognition and learning. The models are tools in the development of general theories.
Advocates of the DRC approach are skeptical about discovering general principles; the main criterion for success is how many empirical phenomena a model can simulate. I'll review the strengths and weaknesses of each approach. The major conclusion is that the model-fitting approach results in overfitting and models that fail to generalize. The connectionist approach has its own limitations, but has proved more successful in identifying general principles that are
not tied to details of individual implemented models. |
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| oncancel | Exceptionnellement un mardi |
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| responsibles | Pélissier |
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