Formalization of different learning strategies in a continuous learning framework

While the ability to learn on its own is an important feature of a learning agent, another, equally important feature is ability to interact with its environment and to learn in an interaction with other cognitive agents and humans. In this paper we analyze such interactive learning and define several learning strategies requiring different levels of tutor involvement and robot autonomy. We propose a new formal model for describing the learning strategies. The formalism takes into account different levels and types of communication between the robot and the tutor and different actions that can be undertaken. We also propose appropriate performance measures and show the experimental results of the evaluation of the proposed learning strategies.