Accelerating reinforcement learning on a robot by using subgoals in a hierarchical framework

Reinforcement learning is a way to learn control tasks by trial and error. Even for simple motor control tasks, however, this can take a long time. We can speed up learning by using prior knowledge, but this is not always available, especially for an autonomous agent. One way to add limited prior knowledge is to use subgoals, defining points...

The Effects of Large Disturbances on On-Line Reinforcement Learning for aWalking Robot

Reinforcement Learning is a promising paradigm for adding learning capabilities to humanoid robots. One of the difficulties of the real world is the presence of disturbances. In Reinforcement Learning, disturbances are typically dealt with stochastically. However, large and infrequent disturbances do not fit well in this framework; essentially,...

Augmented Reality for Art, Design and Cultural Heritage: System Design and Evaluation

This paper describes the design of an optical see-through head-mounted display (HMD) system for Augmented Reality (AR). Our goals were to make virtual objects “perfectly” indistinguishable from real objects, wherever the user roams, and to find out to which extent imperfections are hindering applications in art and design. For AR, fast and...