Title: Topological Path Planning for Mobile Robot Applications   Abstract: Many path planning problems in mobile robot applications can be solved more efficiently in the topological space. By using the language of topology, the richer spatial information failed to captured by graph/grid-based map representations can be explicitly expressed and exploited. With that, it is possible [...]

Title: Deep Reinforcement Learning with Prior Knowledge   Abstract: Deep reinforcement learning has been applied to many domains from computer games, natural language processing, recommendation systems to robotics.  While model-free reinforcement learning algorithms are promising approaches to learning policies without knowledge of the system dynamics, they usually require much more data. In this thesis, we [...]