Department of Brain & Cognitive Sciences, University of Rochester, USA
Wednesday 13 May 2009
Seminar Room B10 (Basement)
Alexandra House, 17 Queen Square, London, WC1N 3AR
Is Human Learning Optimal?
We address the question "Is human learning optimal?" in two research projects. In the first project, human subjects performed a perceptual matching task in which they attempted to convert the shape of a comparison object into the shape of a target object. To do this efficiently required knowledge of the causal relations among a set of underlying hidden or latent variables. Our results indicate that subjects did achieve near-optimal performance levels, and they did acquire good knowledge of the causal relations. In the second project, subjects performed a visual pattern discrimination task in which patterns were linear combinations of a set of arbitrary "basis features". Associated with each feature was a noise parameter. Features with small noise values were reliable information sources for the discrimination task, whereas features with large noise values were unreliable sources. Subjects learned to combine the information from the features in a near-optimal manner. Both projects suggest that human learning is both optimal and non-optimal. It is optimal in the sense that it leads to near-optimal performances. It is non-optimal in the sense that learning requires many more training trials than required by an ideal learner.