Researchers have developed a new reinforcement learning approach that leverages crowdsourced feedback to guide AI agents in learning complex tasks.
This approach allows for faster learning despite the potential errors in the data gathered from nonexpert users.
Feedback can be gathered asynchronously from nonexpert users around the world, making it scalable and accessible to a larger community.