Computational Explorations of Cognitive Development

Many of the problems of children's cognitive development have been difficult and longstanding. Among these are issues of how children represent knowledge, whether stages exist, and how children achieve transitions between stages. Despite a century of scientific evidence on child development, comprehensive theoretical understanding of these issues has remained elusive. Part of the reason is that the problems of psychological development are too complex for traditional verbal theories of development. Nonetheless, it has become clear in recent years that considerable leverage on these problems can be gained by applying computational modeling, particularly using artificial neural networks. This is because computational modeling is a good way to capture complex processes, neural networks capture developmental phenomena in a natural way, and successful models can be examined in detail to discover insights into the phenomena that they simulate (Shultz, 2001).