Adjuncts and arguments exhibit different syntactic behaviours, but modelling this difference in minimalist syntax is challenging: on the one hand, adjuncts differ from arguments in that they are optional, transparent, and iterable, but on the other hand they are often strictly ordered, reflecting the kind of strict selection seen in argument…

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of…

Humans are remarkably sensitive to the statistical structure of language. However, different mechanisms have been proposed to account for such statistical sensitivities. The present study compared adult learning of syntax and the ability of two models of statistical learning to simulate human performance: Simple Recurrent Networks, which learn by…

We present data from an artificial language domain that suggest new contributions to the theory of syntactic triggers. Whether a learning algorithm is capable of matching the achievements of child learners depends in part on how much parametric ambiguity there is in the input. For practical reasons this cannot be established for the domain of all…

The first of three articles on the ways in which people formulate their observations, this paper considers the basic assumptions of both syntactic and paradigmatic models of cognition and their applications in natural (i.e., human) and artificial (i.e., computer) information processing. The analysis begins with background information on the nature…

According to "noun-cue" models, arbitrary linguistic categories, like those associated with case and gender systems, are difficult to learn unless members of the target category (i.e., nouns) are marked with phonological or semantic cues that reliably co-occur with grammatical morphemes (e.g., determiners) that exemplify the categories. "Syntactic…