Resumen de Bootstrapping autonomous skill learning in the MDB cognitive architecture
Alex Romero, Francisco Javier Bellas Dublang, Jose Alberto Becerra Becerra, Richard J. Duro Fernández 
This paper is concerned with motivation in autonomousrobots. In particular we focus on the basic structure that is necessary for bootstrapping the initial stages of multiple skill learning within the motivational engine of the MDB cognitive architecture. To this end, taking inspiration from a series of computational models of the use of motivations in infants, we propose an approach that leverages two types of cognitive motivations: exploratory and proficiency based. The latter modulated by the concept of interestingness. We postulate that these make up the minimum set of motivational components required to initiate the unrewarded learning of a skill toolbox that may later be used in order to achieve operational goals.The approach is illustrated through an experiment with a real robot that is learning skills in a real environment.
