PDP highlights the parallels between connectionist models and neural coding in the brain, while also dismissing localism.
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Another form of connectionist model was the relational network framework developed by the linguist Sydney Lamb in the 1960s.
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Recently symbolic and connectionist models have been combined, making it possible to take advantage of both forms of explanation.
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His present work focuses on learning, memory processes, and psycholinguistics, still within the framework of connectionist models.
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Also, a completely different approach, one not based on symbolic reasoning but on a connectionist model has also been extremely productive.
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Attempts have been made to model the developmental process of language acquisition in children from a computational angle, leading to both connectionist models.
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All gradient descent learning in connectionist models involves changing each weight by the partial derivative of the error surface with respect to the weight.
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The connectionist model evolved out of Parallel Distributed Processing framework that formulates a metatheory from which specific models can be generated for specific applications.
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In the philosophy of mind, he is known for his attempts to apply connectionist models of coherence to theories of human thought and action.
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Many connectionist models of the brain have been developed in which the processes of language learning and other forms of representation are highly distributed and parallel.
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