Supervisory Control of Learning and Adaptive Systems
Papers from the AAAI Workshop
Mike Rosenstein and Mohammad Ghavamzadeh, Program Cochairs
With supervisory control, a human operator intermittently takes control of a process that is otherwise controlled by a computer. Supervisory control involves both autonomy and intelligence, although the latter is normally attributed solely to the human operator. One goal of this workshop, therefore, is to bring together researchers in robotics, machine learning, human-computer interaction and other areas to explore the role of supervisory control for AI systems, especially for systems where both human and machine share the ability to learn and adapt to changing circumstances. In the past, supervisory control has focused primarily on traditional applications of telerobotics, such as hazardous waste disposal, planetary and undersea exploration, and remote surveillance and repair. These applications remain important areas of research today, although in recent years supervisory control has become much more pervasive than we often realize. Assistive technology for the physically handicapped, software agents for electronic commerce, and education technology for the modern classroom are all examples where shared control by human and machine will have increasing societal impact. Thus, another goal of this workshop is to identify real-world applications where the combination of supervisory control and AI will have the most impact.