Abstract
The goal of this special issue is twofold: first, to acquaint members of the machine learning community with the latest results in connectionist language learning, and second, to make these five inter-related papers available in a single publication as a resource for others working in the area. In the remainder of this introduction I will sketch what it is that I think the connectionist approach offers us, and how the papers in this special issue advance the state of the art . But this is not going to be a cheerleading piece about the wonders of “brain-style computation” and the imminent death of symbolic AI. Rather, I hope to tempt the reader into examining some novel ideas that expand the current scope of AI.
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© 1991 Springer Science+Business Media New York
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Touretzky, D.S. (1991). Introduction. In: Touretzky, D. (eds) Connectionist Approaches to Language Learning. The Springer International Series in Engineering and Computer Science, vol 154. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4008-3_1
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DOI: https://doi.org/10.1007/978-1-4615-4008-3_1
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