Robot simulations are faster and more economical than real physical mobile robots. Any simulation can be thought of as 2 coupled Turing machines, one, agent p, representing the robot, and the other, environment q, representing the environment:
At any time step the robot sees an input vector x' and may receive rewards r. It also produces an output vector y.
The environment at any time step receives an input vector y and generates a response vector x' r. An especially simple environment is nothing more than a case-based reasoner or approximate look up table.
Asa H agents (serving as agent p) can be taught certain concepts/behaviors in such a simulator.