Prediction-error driven learning: the engine of change in cognitive development

Summary form only given. Since the introduction of powerful connectionist learning procedures such as back propagation, our group has been studying the use of such procedures as a mechanism for cognitive development. The models can be viewed as capturing Piaget´s idea that development is essentially an experience driven process, dependent of the adjustment of schemas to assimilate disparities between expectations and observations. Among the issues that have been addressed with these models are the following: (1) Is an initial naive domain theory required to allow a learner to interpret experience in a given domain? (2) Why does learning appear to occur in stages, punctuated by plateaus? (3) what does it mean to be ´ready to learn´? (4) Is it necessary to start small in learning, and if so when and why? (5) Why are there critical or sensitive periods in learning; why is it sometimes easier to learn when a system is ´young´ or inexperienced?.