Shastri, L., & Chang, S. (1999). A spatiotemporal connectionist model of algebraic rule-learning (TR-99-011). Berkeley, California: International Computer Science Institute.  Home/Search   Document Details and Download   Summary   Related Articles

....overlap with the items that appeared in training (p. 79) In the first simulation, we demonstrate that SRNs can indeed fit the data from Marcus et al. Other researchers have constructed neural network models specifically to simulate the Marcus et al. results (Altmann Dienes, 1999; Elman, 1999; Shastri Chang, 1999; Shultz, 1999) In contrast, we do not build a new model to accommodate the results, but take an existing SRN model of speech segmentation (Christiansen et al. 1998) and show how this model without additional modification provides an explanation for the results. The Christiansen et al. ....

....the increased duration of time between the occurrence of these variables) From this property, one can predict that lengthening the time between variables should not affect the preference for inconsistent items. Indeed, the connectionist implementation of the rule based approach found in the Shastri Chang (1999) model would appear to make this prediction. A lengthening of the pauses between words should, however, have a different effect on our model. In the model, the preference for inconsistent items observed by Marcus et al. is explained in terms of differential segmentation performance. Lengthening ....

Shastri, L., & Chang, S. (1999). A spatiotemporal connectionist model of algebraic rule-learning (TR-99-011). Berkeley, California: International Computer Science Institute.

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