Interactive Learning and Interventional Representations

We rethink the principles of interactive models of learning, exploring the role of causal modelling in bridging the gap between observational and interventional learning. The ultimate goal is to understand the organizing principles underlying robust intelligent behaviour, and to enable reliable learning-based decision systems for high-stakes real-world applications.

  • Principles of learning-in-the-loop systems
  • Online and reinforcement learning
  • Causal inference
  • Interacting learning systems (multi-agent learning, games, networks)


Workshops organized by the program

26 - 28 February 2024: ELLIS Program Workshop Interactive Learning and Interventional Representations

A group of international researchers gathered at the Oberwolfach Research Institute for Mathematics (MFO) in southern Germany for an in-depth meeting on the program's research areas, fostering exchange and collaborations among scientists in Europe. The workshop was funded by the state of Baden-Württemberg (Germany) and organized in collaboration with the ELLIS Institute Tübingen and the Max-Planck-Institut für Intelligente Systeme. Read a detailed summary here.