On-line learning for Micro-Object Manipulation.
Résumé
This chapter presents the application of a reinforcement learning algorithm to learning on-line how to manipulate micro-objects. What makes this application original is that the action policy has been learned not thanks to a simulator but by controlling the real process. This work related to reinforcement learning for micro-robotics has been conducted at the Automatic control and Micro-Mechatronic Systems department of the FEMTO-ST Institute (Besançon - France).