Statistics for Machine Learning

Robo soccer

Robotics as a reinforcement learning domain differs considerably from most well-studied reinforcement learning standard problems. Problems in robotics are often best represented with high-dimensional, continuous states and actions. 10-30 dimensional continuous actions common in robot reinforcement learning are considered large. The application of reinforcement learning on robotics involves so many sets of challenges, including a noise-free environment, taking into consideration real physical systems, and learning by real-world experience could be costly. As a result, algorithms or processes needs to be robust enough to do what is necessary. In addition, the generation of reward values and reward functions for the environments ...