Understanding how humans and AI or robotic agents can work together effectively requires a shared foundation for experimentation. A University of Michigan-led team developed a new taxonomy to serve as a common language among researchers, then used it to evaluate current testbeds used to study how human-agent teams will perform.
Originally published by Tech Xplore https://techxplore.com/robotics-news/