2017
Neural networks for incremental dimensionality reduced reinforcement learning
IROS 2017poster
State-of-the-art personal robots must perform complex manipulation tasks to be viable in assistive scenarios. However, many of these robots, like the PR2, use manipulators with high degrees-of-freedom. The complexity of these robots lead to large dimensional state spaces, which are difficult to full…