1 Evolving Connectionist Models to Capture Population Variability Across Language Development: Modelling Children’s Past Tense Formation

Children’s acquisition of English past tense has been widely studied as testing ground for theories of language development, mostly because it comprises a set of quasi-regular mappings. English verbs are of two types: regular verbs, which form their past tense based on a productive rule, and irregular verbs, which form their past tenses through exceptions to that rule. Although many connectionist models exist for capturing language development, very few consider individual differences. In this paper, we explore the use of populations of artificial neural networks (ANNs) that evolve according to Behavioural Genetics principles in order to create computational models capable of capturing the population variability exhibited by children in acquiring English past tense verbs. Literature in the field of Behavioural Genetics views variability in children’s learning in terms of genetic and environmental influences. In our model, the effects of genetic influences are simulated through variations in the neuro-computational properties of ANNs, and the effects o