This is a diagram of an actual Learned State Machine from one robot in one corner learning experiment. (Note: these data are from a different experiment series than the Distance and Entropy graphs shown before).

At the beginning of the experiment the machine was defined as the two top states s6 and s7. As time goes on and experience collects the s7 state is split into copies of itself and the copies are 'allowed' to learn on their own. What they learn is a different set of responses to sequential bumper inputs. This can be seen in the sub-states by following the colored paths. Instead of "blindly" using the Back-up-and-turn-away response, the robot has learned that the sequence of inputs that indicate a corner should initiate a strategy of Back-up-and-turn-the-same-direction until it escapes.

Another measure of structure is how many states a machine has. This diagram is not entirely indicative because it hasn't been reduced to a minimal set, but it does show that order and structure have increased.