Virtual developmental robotics in a social VR environment
The aim of this project is to build a framework to train AI agents in social virtual reality (VR) environments. The main motivations are to explore how social interactions with humans can benefit the development of more human-like artificial intelligence, and whether it has the potential to pose a systematic risk to human society. This idea builds on top of research in developmental robotics, reinforcement learning, and psychology. However, research in human-AI social interaction has been limited by the use of expensive robots and sensing systems. We propose to massively scale up and lower the barrier for these types of experiments by using new VR technologies.
Our approach is to build a software framework on top of an existing social VR application (e.g. NeosVR, VRChat), and to test this framework by experimenting with agents which implement novel and state-of-the-art learning techniques such as algorithms based on intrinsic motivation and curiosity, which have shown a lot of promise on efficiently learning complex behavior in rich environments Oudeyer 2018