Convergence properties of the eventvalue function for the twolink pendulum are shown in Figure 5. The experiment concerns crude discretization of the state space. No change of the parameters of the pendulum are made. However, crude discretization of the environment and a robust controller, which is part of the environment, exhibits itself as a varying environment.
The theorems of Section 3 concern supremum norm. Two curves about the supremum norm are shown in Figure 5A, one with the SDS controller turned off () and another one with the SDS controller on . Convergence occurs for learning with the SDS controller `on'.^{10} Interestingly, convergence is faster with the SDS controller than without it. This is a consequence of the larger variety of actions available when the robust controller is applied.
The square norm against the last eventvalue function of this series of experiments (Figure 5B) may provide insight into the performance of the twolink pendulum. The performance of the pendulum can be characterized by the average task duration and the standard deviation of task duration during the course of learning (Figure 5C). There is a clear advantage for the case against learning without the robust controller.
