Attractor-based computation with reservoirs for online learning of inverse kinematics
Felix Reinhart, Jochen J. Steil · 2009
Abstract. We implement completely data driven and efficient online learning from temporally correlated data in a reservoir network setup. We show that attractor states rather than transients are used for computation when learning inverse kinematics for the redundant robot arm PA-10. Our findings shade also light on the role of output feedback. 1