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