The students are able to:
- analyze scientific papers in the field of Human-Robot Collaboration
- reflect on what is required for human-machine alignment in human-robot collaborative systems from a technical and ELSE perspective
- apply agreement technologies and HART methods for analysing and modelling a collaborative human-robot system
- perform an empirical study to understand the requirements for human-robot collaboration
- synthesize insights from the literature and other sources to develop their own vision of the future of human-robot collaboration and the role of human-machine alignment in this
As robots and other AI systems are getting more and more interwoven into our society and daily lives, it becomes increasingly important that we can effectively collaborate with such systems, and that they are developed in a responsible way. In this course, we address these challenges, providing insight into computational models, design approaches, user experience and connected ELSE aspects of human-robot collaboration and hybrid intelligence.|
The topics of the course include the following:
- Agreement technologies: computational models for regulating and increasing the effectiveness of societies of interacting software agents centred around the notion of ‘agreement’ for example about which course of action to take. Including: normative multiagent systems, argumentation frameworks, and ontology alignment approaches.
- Human-machine alignment: how can we ensure that robots and other AI applications behave in alignment with human and societal needs and values? Including: responsible AI, value alignment, and shared mental models.
- Human-agent/robot teamwork (HART): how can we make automation a team player? Including: autonomy-centred approaches to HART, such as adjustable autonomy and shared control, and coactive design which is centred around human-machine interdependence.
- Social robotics: how to create socially intelligent robots? Including: socially normative robot behaviour, cross-cultural design, user modelling