Mechanisms for Inductive Learning: from Base-Learning to Meta-Learning

This paper briefly surveys the state of the art of a particular mechanism of learning: induction. We discuss inductive mechanisms, drawing attention to the foundation of generalisation success and its limitations. The distinction between base-learning and meta-learning approaches is pointed out in order to better identify the peculiar attributes of current learning strategies. We examine the possibilities to increase the efficiency of learning algorithms via a metalearning approach, mentioning also some new research lines for further developments on this topic.