  A remarkable feature of human beings is their capacity for creative
behaviour, referring to their ability to react to problems in ways that are
novel, surprising, and useful. Transformational creativity is a form of
creativity where the creative behaviour is induced by a transformation of the
actor's conceptual space, that is, the representational system with which the
actor interprets its environment. In this report, we focus on ways of adapting
systems of learned representations as they switch from performing one task to
performing another. We describe an experimental comparison of multiple
strategies for adaptation of learned features, and evaluate how effectively
each of these strategies realizes the adaptation, in terms of the amount of
training, and in terms of their ability to cope with restricted availability of
training data. We show, among other things, that across handwritten digits,
natural images, and classical music, adaptive strategies are systematically
more effective than a baseline method that starts learning from scratch.
