Towards Corrective Deep Imitation Learning in Data Intensive Environments: Helping robots to learn faster by leveraging human knowledge

Interactive imitation learning refers to learning methods where a human teacher interacts with an agent during the learning process providing feedback to improve its behaviour. This type of learning may be preferable with respect to reinforcement learning techniques when dealing with real-world problems. This fact is especially true in the case...