GloCAL: Glocalized Curriculum-Aided Learning of Multiple Tasks with Application to Robotic Grasping
Anil Kurkcu,Cihan Acar,Domenico Campolo,Keng Peng Tee,Anil Kurkcu,Cihan Acar,Domenico Campolo,Keng Peng Tee
The domain of robotics is challenging to apply deep reinforcement learning due to the need for large amounts of data and for ensuring safety during learning. Curriculum learning has shown good performance in terms of sample-efficient deep learning. In this paper, we propose an algorithm (named GloCAL) that creates a curriculum for an agent to learn multiple discrete tasks, based on clustering task...
