Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schem...
In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...
—Learning control is a concept for controlling dynamic systems in an iterative manner. It arises from the recognition that robotic manipulators are usually used to perform repeti...
— Because a delay tolerant network (DTN) can often be partitioned, routing is a challenge. However, routing benefits considerably if one can take advantage of knowledge concerni...
— This paper focuses on the design of a robust tube-based Model Predictive Control law for the control of constrained mobile robots. A time-varying trajectory tracking error mode...
Ramon Gonzalez, Mirko Fiacchini, Jose Luis Guzman,...