ABSTRACT
Computational models are computer programs that mimic some aspect of psychological processing. This chapter presents the computational modeling approach and discusses what it can contribute to our understanding of cognitive development in general and to word learning in particular. It explains the basic principles of one widely used type of computational model—artificial neural networks and reviews several word learning models and their contributions to our understanding of this process. In developmental psychology, computational models are often used to account for the change in cognitive abilities across age, allowing researchers to examine the effects of accumulating experience and changes in learning processes on the observed developmental trajectories. The chapter describes the principles of artificial neural networks and specifically the three most common types used in models of word learning. In supervised learning, a model receives an input and has to learn to generate a specific output as a response.
