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. In investigating human cognitive and perceptual development, connectionist models of learning and representation are presented alongside various aspects of language and kwledge acquisition. Some contributors describe work within a traditional artificial intelligence framework and others show how computer programs have been designed to mimic particular human developmental processes. Chapters in the final section focus on what is currently kwn 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 developmental psycholinguists as well as those with an interest in connectionist/neural network research.
Philip Quinlan is an experienced Senior Lecturer in Psychology at the University of York, and the author of a previous book on Connectionism and Psychology.