  Social, supervised, learning from others might amplify individual, possibly
unsupervised, learning by individuals, and might underlie the development and
evolution of culture. We studied a minimal model of the interaction of
individual unsupervised and social supervised learning by interacting agents.
Agents attempted to learn to track a hidden fluctuation "source", which,
linearly mixed with other masking fluctuations, generated observable input
vectors. Learning was driven either solely by direct observation of inputs
(unsupervised, Hebbian) or, in addition, by observation of another agent's
output (supervised, Delta rule). To enhance biological realism, the learning
rules were made slightly connection-inspecific, so that incorrect learning
sometimes occurs. We found that social interaction can foster both correct and
incorrect learning. Useful social learning therefore presumably involves
additional factors some of which we outline.
