Host: Kim Plunkett
Computational modeling of human learning and cognitive development
Abstract: One of the major unsolved problems in cognitive development concerns the nature of transition mechanisms. How does the child progress from one cognitive stage to the next? We find that cognitive transitions can be modeled, and thus better understood, with constructive neural networks that grow as well as learn. We extended and applied Fahlman's cascade-correlation algorithm, which recruits new hidden units when network error cannot be further reduced by quantitative adjustment of connection weights, to model a wide range of psychological phenomena in development. This modeling work sheds light on a variety of related issues. How is knowledge represented at various developmental stages? What accounts for the particular orders of stages? Why does development take a particular shape over time? How to account for the typical mistakes that children make before they get it right? What is the difference between learning and development? How does past knowledge guide new learning? How might neural systems accomplish Bayesian inference and learning, while sometimes deviating from Bayes’ rule? How close are we to capturing the autonomous nature of biological learners?
Bio: Thomas Shultz (PhD Yale, Psychology) is Professor of Psychology and Associate Member of the School of Computer Science at McGill. He teaches courses in Computational Psychology and Cognitive Science. He is a Fellow of the Canadian Psychological Association, and a co-founder of McGill’s undergraduate programs in Cognitive Science and Neuroscience. Research interests include connectionism, cognitive science, cognitive development, evolution and learning, and relations between knowledge and learning. He has over 220 research publications in these areas. He is a Member of the IEEE Neural Networks Society Autonomous Mental Development Technical Committee and Chair of the AMD Task Force on Developmental Psychology. Journal editorships include: Editorial Board of Computational Intelligence and Neuroscience, Associate Editor of the IEEE Transactions on Autonomous Mental Development, and Review Editor of Frontiers in Neurorobotics.