ABSTRACT
The degree to which the behavior of PDP models of pattern associations (Rumelhart & McClelland, 1986; 1987) approximates children's acquisition of inflectional morphology has recently been highlighted in discussions of the applicability of PDP to the study of human cognition and language (Pinker & Mehler, 1988). In this paper, we attempt to eliminate many of the limitations of the R&M model, adopting an empirical approach to the analysis of learning (hit rate and error type) in two sets of simulations in which vocabulary structure (token frequency) and the presence of phonological subre-gularities are manipulated. A 3-layer back propagation network is used to implement a pattern association task with strings that are analogous to four types of present and past tense English verbs. We overview resulting “competitions” when strings are randomly assigned to verb classes, in particular, the conditions under which different overgeneralization errors (both “pure” and “blended”) are produced. In a second set of simulations, identical type and token frequencies are used, but strings are assigned to the identity and vowel change classes on the basis of phonological shape of the stem. Phonological cues are exploited by the system leading to overall improved performance. However, overgeneralizations continue to be observed in similar conditions. Token frequency works together with phonological subre-gularities to determine patterns of learning, including the conditions under which “rule-like” behavior will and will not emerge. The results are discussed with reference to behavioral data on children's acquisition of the English past tense.
