Self-understanding and self-extension: a systems and representational approach

There are many different approaches to building a system that can engage in autonomous mental development. In this paper we present an approach based on what we term \em self-understanding, by which we mean the use of explicit representation of and reasoning about what a system does and doesn't know, and how that understanding changes under action. We present a coherent architecture and a set of representations used in two robot systems that exhibit a limited degree of autonomous mental development, what we term \em self-extension. The contributions include: representations of gaps and uncertainty for specific kinds of knowledge, and a motivational and planning system for setting and achieving learning goals.