AUTHOR=Santucci Vieri G., Baldassarre Gianluca , Mirolli Marco TITLE=Which is the best intrinsic motivation signal for learning multiple skills? JOURNAL=Frontiers in Neurorobotics VOLUME=7 YEAR=2013 URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2013.00022 DOI=10.3389/fnbot.2013.00022 ISSN=1662-5218 ABSTRACT=

Humans and other biological agents are able to autonomously learn and cache different skills in the absence of any biological pressure or any assigned task. In this respect, Intrinsic Motivations (i.e., motivations not connected to reward-related stimuli) play a cardinal role in animal learning, and can be considered as a fundamental tool for developing more autonomous and more adaptive artificial agents. In this work, we provide an exhaustive analysis of a scarcely investigated problem: which kind of IM reinforcement signal is the most suitable for driving the acquisition of multiple skills in the shortest time? To this purpose we implemented an artificial agent with a hierarchical architecture that allows to learn and cache different skills. We tested the system in a setup with continuous states and actions, in particular, with a kinematic robotic arm that has to learn different reaching tasks. We compare the results of different versions of the system driven by several different intrinsic motivation signals. The results show (a) that intrinsic reinforcements purely based on the knowledge of the system are not appropriate to guide the acquisition of multiple skills, and (b) that the stronger the link between the IM signal and the competence of the system, the better the performance.