The RLeap Project

Representation Learning for Acting and Planning

The RLeap project aims at bringing together two of the main current research threads in Artificial Intelligence:
  • Data-based learners capable of inferring behavior and functions from experience and data.
  • Model-based solvers capable of tackling well-defined but intractable models.
Our research is focused on the integration of learners and solvers in the context of acting, addressing the problem of learning first-order symbolic representations from raw perceptions alone without using any specific prior symbolic knowledge. Read more about the project.

Who are we?

The RLeap project started in 2020 and is participated by researchers from the Artificial Intelligence and Machine Learning Research Group at Universitat Pompeu Fabra, Spain, and from the Artificial Intelligence and Integrated Computer Systems division at Linköping university, Sweden. The project is funded by an Advanced ERC grant and the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP), among other sources. Read more about our team.