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

no code implementations • 7 Jul 2020 • Ithan Moreira, Javier Rivas, Francisco Cruz, Richard Dazeley, Angel Ayala, Bruno Fernandes

We compare three different learning methods using a simulated robotic arm for the task of organizing different objects; the proposed methods are (i) deep reinforcement learning (DeepRL); (ii) interactive deep reinforcement learning using a previously trained artificial agent as an advisor (agent-IDeepRL); and (iii) interactive deep reinforcement learning using a human advisor (human-IDeepRL).

reinforcement-learning Reinforcement Learning (RL)