Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination
Abdalkarim Mohtasib,Gerhard Neumann,Heriberto Cuayáhuitl,Abdalkarim Mohtasib,Gerhard Neumann,Heriberto Cuayáhuitl
Learning robotic tasks in the real world is still highly challenging and effective practical solutions remain to be found. Traditional methods used in this area are imitation learning and reinforcement learning, but they both have limitations when applied to real robots. Combining reinforcement learning with pre-collected demonstrations is a promising approach that can help in learning control pol...
