AI*MAN Lab

Transparent & Traceable AI in Human-AI Teamwork

The AI*MAN Lab is studying and trying to improve many aspects of human-AI teamwork. Consider, for example, a search-and-rescue team where autonomous drones and human rescuers collaborate to map unknown search area, localise victims, and share search-and-rescue tasks efficiently. Alternatively, consider a social robot that can interact creatively and in a human-like way, assisting and helping people with conditions such as autism or dementia. Such a robot would be able to understand what a human might think or feel, and explain itself to a user in return. 

Experience shows that excellent performance improvements are possible in industry, education, healthcare and many more applications when AI and humans work together, exploiting both human instincts for effective decisions in unknown situations and fast and logical AI decisions.In a human-AI team, decisions made by either the human or the AI agent may seem illogical to the other party if only individual goals are considered, so a mutual understanding of each other’s decision-making processes and actions is critical in pursuit of common team goal(s). 

Part of our research therefore involves modelling the way humans think and building logical models that will help the AI agents to understand their human teammates. We develop AI agents able to take decisions that are good for the entire team and make these decisions transparent to humans.

The AI*MAN Lab is part of the TU Delft AI Labs programme.

The Team

Directors

PhD's

Associated faculty

Education

Courses

2022/2023  

2020/2021  

2019/2020  

Master projects

Ongoing  

  • The impact of AI expressing feelings/emotions with explanation in human-robot teamwork, Myrthe Tielman, Sunwei Wang (2023/2024) 
  • Hybrid Search-and-Rescue Robots, Anahita Jamshidnejad, Berkay Yaz?c?o?lu (2023/2024) 
  • Multi-Agent Outdoor Search-and-Rescue, Anahita Jamshidnejad, Craig Maxwell (2023/2024) 
  • Data Fusion for Search-and-Rescue, Anahita Jamshidnejad, Bernardo Henriques (2023/2024) 
  • Formalizing Theory of Mind mechanisms and tasks for reinforcement learning, Myrthe Tielman, Jan-Willem van Rhenen (2022/2023) 

Finished  

Partners