Minimal model of associative learning for cross-situational lexicon acquisition
نویسندگان
چکیده
An explanation for the acquisition of word-object mappings is the associative learning in a crosssituational scenario. Here we present analytical results of the performance of a simple associative learning algorithm for acquiring a one-to-one mapping between N objects and N words based solely on the co-occurrence between objects and words. In particular, a learning trial in our learning scenario consists of the presentation of C + 1 < N objects together with a target word, which refers to one of the objects in the context. We find that the learning times are distributed exponentially and
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عنوان ژورنال:
- CoRR
دوره abs/1204.1564 شماره
صفحات -
تاریخ انتشار 2012