Connectionist Models of Development

Connectionist Models of Development

Connectionist Models of Development

Connectionist Models of Development

Synopsis

Connectionist Models of Development is an edited collection of essays on the current work concerning connectionist or neural network models of human development. The brain comprises millions of nerve cells that share myriad connections, and this book looks at how human development in these systems is typically characterised as adaptive changes to the strengths of these connections. The traditional accounts of connectionist learning, based on adaptive changes to weighted connections, are explored alongside the dynamic accounts in which networks generate their own structures as learning proceeds. Unlike most connectionist accounts of psychological processes which deal with the fully-mature system, this text brings to the fore a discussion of developmental processes. To investigate human cognitive and perceptual development, connectionist models of learning and representation are adopted alongside various aspects of language and knowledge acquisition. There are sections on artificial intelligence and how computer programs have been designed to mimic the development processes, as well as chapters which describe what is currently known about how real brains develop. This book is a much-needed addition to the existing literature on connectionist development as it includes up-to-date examples of research on current controversies in the field as well as new features such as genetic connectionism and biological theories of the brain. It will be invaluable to academic researchers, post-graduates and undergraduates in developmental psychology and those researching connectionist/neural networks as well as those in related fields such as psycholinguistics.

Excerpt

Sylvain Sirois

Department of Psychology, University of Manchester, uk

Thomas R. Shultz

Department of Psychology and School of Computer Science, McGill University, Montreal, Canada

The significance of Jean Piaget's contribution to the study of cognitive development has gained the status of a truism. Even today, some of his original ideas such as object permanence spawn significant theoretical debates (e.g. Baillargeon, 2000; Bogartz et al., 2000), generating contributions from connectionist and other computational approaches as well (see Mareschal, 2000, for a review). However, Piaget's heuristic value is not limited to the identification of several robust empirical regularities, however useful these may be to benchmark developmental theories.

Piaget's contribution to the study of cognitive change can be divided, for convenience, into four distinct areas. First, as alluded to in the previous paragraph, his work led to the identification of several robust findings about infants' and children's cognitive abilities. Notions such as object permanence, conservation, and seriation, for example, spawned hundreds of studies that replicated, extended, or refined Piaget's earlier work.

Second, his many original findings stemmed from a novel methodological approach that stressed underlying cognitive operations rather than the usual success or failure assessment of performance. in the clinical interview, for instance, a child's errors prompt researchers to inquire about the justifications for the child's behaviour. These justifications provide insights into the underlying conceptual system of the child that elude traditional, quantitative assessment approaches.

Third, Piaget proposed a unifying framework to discuss cognitive competence. His structural theory argued that any level of cognitive functioning

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