The rational expectations hypothesis assumes—primarily for reasons of internal consistency—that agents possess complete knowledge of all relevant probability distribution functions. When attempts are made to incorporate learning into these models, often in response to longstanding criticism, it is invariably a highly constrained form of learning. This type of learning excludes the truly unexpected or surprising. […]