Reinforcement learning methods are useful for robot learning, but become slow when robots possess many degrees of freedom. We suggest equipping robots with fast on-board simulators, in order to accelerate learning. Such simulators will resemble forms of consciousness, enabling the robots to perform run-time trials in a simulated world, rather than tediously performing them in practice. We have ...
