The research topics of the RLeap Lab include:
- Learning representations for planning
- Planning models, algorithms, and techniques
- Planning and reinforcement learning
- Generalized planning
- Model-based vs. model-free intelligence
The chair hosts two other research groups:
We are seeking highly motivated and talented doctoral students, postdoctoral researchers and student assistents eager to make a difference in these problems, with experience and interest in areas such as deep learning, reinforcement learning and planning, logic and knowledge representation, combinatorial optimization and SAT. The doctoral students and postdoctoral researchers will pursue their research in the context of these broad goals, on specific themes that will be a function of their background, skills, and interests, and our research agenda.