Robot gains Social Intelligence through Multimodal Deep Reinforcement Learning

Human-robot interaction (HRI) is an emerging field of research with the aim to integrate robots into human social environments. One of the biggest challenges in the development of social robots is to understand human social norms [1]. It is therefore essential for social robots to possess deep models of social cognition, and be able to learn and adapt in accordance with their shared experiences with human partners. Most of the social robots to date are either preprogrammed, or are controlled by teleoperation or semiautonomous teleoperation [2], and do not possess the ability to learn and update themselves. Designing an adaptable and autonomous sociable robot is particularly challenging, as the robot needs to correctly interpret human behaviors as well as respond appropriately to them.