Acquiring knowledge about the underlying structures of the environment presents a number of challenges for a naive learner. These challenges include the absence of reinforcement to guide learning, the presence of numerous information sources from which only a select few are relevant, and the uncertainty about when an underlying structure may have undergone a change. A crucial implication of these challenges is that the naive learner must make implicit decisions about when to generalize to novel inputs and when to restrict generalization because there are multiple underlying structures. An historical perspective on these challenges is presented and some potential solutions are proposed.
Keywords: familiarity preference; generalization; novelty preference; rule learning; statistical learning.