Sample-efficient Deep Reinforcement Learning with Imaginary Rollouts for Human-Robot Interaction

Mohammad Thabet, Massimiliano Patacchiola, Angelo Cangelosi

Deep reinforcement learning has proven to be a great success in allowing agents to learn complex tasks. However, its application to actual robots can be prohibitively expensive. Fu…