Researchers have developed a reinforcement learning approach that uses crowdsourced feedback to guide AI agents.
This approach allows the AI agent to learn more quickly and gather feedback asynchronously from nonexpert users around the world.
The traditional method of designing reward functions by expert researchers is time-consuming and not scalable for teaching robots different tasks.