Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment

Understand

Robots are extending their presence in domestic environments every day, being more common to see them carrying out tasks in home scenarios.

• In the future, robots are expected to increasingly perform more complex tasks and, therefore, be able to acquire experience from different sources as quickly as possible.
• A plausible approach to address this issue is interactive feedback, where a trainer advises a learner on which actions should be taken from specific states to speed up the learning process.
• Moreover, deep reinforcement learning has been recently widely utilized in robotics to learn the environment and acquire new skills autonomously.