Abstract— In their interactions with the world robots inevitably face equivalent action choices, situations in which multiple actions are equivalently applicable. In this paper, ...
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
Building robots can be a tough job because the designer has to predict the interactions between the robot and the environment as well as to deal with them. One solution to cope the...
We show that two cooperating robots can learn exactly any strongly-connected directed graph with n indistinguishable nodes in expected time polynomial in n. We introduce a new typ...
Locally weighted as well as Gaussian mixtures learning algorithms are suitable strategies for trajectory learning and skill acquisition, in the context of programming by demonstrat...