We tested the learnt model for manipulating two different ropes - (i) stiffer white rope and (ii) a softer black rope. Our model is succesfully able to manipulate these ropes into "S" and "L" shapes. This is very interesting because our model was trained using data from only a single red rope. While our model is sucessful at manipulating different ropes into "S" and "L" shapes it is unsucessful at forming knots or the "W" shape. One possible reason for this failure is that the white rope is too stiff to be bent into these shapes. Since our model was trained using only a single (green) background it doesnot generalizes to new backgrounds. If provided with substantially more robot-hours and a greater variety of ropes and environments, our model could in principle learn a more generalizable notion of rope manipulation.