idea what to do in the same case applies to robotic control where for example you would like to train in robotic arm to pick up an object and stack it onto something else well the typical robot has about seven joints that it can move so it's a relatively high action space and if you only give it a positive reward when it's actually successfully stacked a block well by doing random exploration it's never gonna get to see any of that reward and I think it's important to compare this with the traditional supervised deep learning successes that