|Between Exploration and Exploitation in Motor Babbling
Chyon Hae Kim, KantaWatanabe, Shun Nishide, and Manabu Gouko
International Journal of Control, Automation, and Systems, vol. 16, no. 4, pp.1840-1853, 2018
Abstract : "Motor babbling allows an agent sampling trajectory data without a priori knowledge about self-body
and environment dynamics. We discuss about the efficiency of motor babbling through the example of drawing
task. In authors’ insight, natural motor babbling may be featured by exploration and exploitation processes. From
this idea, we propose exploitation babbling and e -greedy babbling. In order to implement the proposed babblings,
we developed dynamics learning tree (DLT). DLT is an online incremental learning algorithm that has constant
calculation order O(1). The proposed exploitation babbling and e -greedy babbling improved the rate of effective
data at 8 and 7 % from previous babbling respectively. e -greedy babbling converged its prediction error fastest
among the three babblings. Using e -greedy babbling, a humanoid robot with wired flexible fingers successfully
drew a figure without a priori knowledge about the dynamics among self-body, pen, and pen tablet."
Drawing, dynamics learning tree, flexibility, learning, motor babbling.