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 self-understanding, by which we mean the explicit representation of and reasoning about what a system does and does not know, and how that knowledge changes under action. We present an architecture and a set of representations used in two robot systems that exhibit a limited degree of autonomous mental development, which we term self-extension. The contributions include: representations of gaps and uncertainty for specific kinds of knowledge, and a goal management and planning system for setting and achieving learning goals.
['Jeremy L. Wyatt', 'Alper Aydemir', 'Michael B. Brenner', 'Marc Hanheide', 'Nick Hawes', 'Patric Jensfelt', 'Matej Kristan', 'Geert-Jan M. Kruijff', 'Pierre Lison', 'Andrzej Pronobis', 'Kristoffer Sjöö', 'Alen Vrečko', 'Hendrik Zender', 'Michael Zillich', 'Danijel Skocaj']
Self-Understanding and Self-Extension: A Systems and Representational Approach