Representation, Learning and Planning Lab
We are the Representation, Learning and Planning Lab at Linköping University. Our research topics of interest include:
- Learning representations for planning
- Planning models, algorithms, and techniques
- Planning and reinforcement learning
- Generalized planning
- Model-based vs. model-free intelligence
- 2022-10-19: David Speck receives the Wolfgang-Gentner-Award for Young Researchers for outstanding scientific achievements in his dissertation awarded by the University of Freiburg.
- 2022-06-01: David Speck joins the group.
- 2022-05-05: Our paper "Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits" receives the ICAPS 2022 Best Paper Award.
- 2022-05-03: Daniel Gnad receives the ICAPS Best Dissertation Award for his thesis "Star-Topology Decoupled State-Space Search in AI Planning and Model Checking".
- 2022-03-01: Our group has five accepted papers at ICAPS 2022.
- 2022-02-01: Daniel Gnad joins the group.
- 2021-08-25: Our paper "Learning Generalized Unsolvability Heuristics for Classical Planning" receives an IJCAI 2021 Distinguished Paper Award.
Our research is primarily supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is a major national initiative for strategically motivated basic research, education and faculty recruitment. The funding is generously provided by the Knut and Alice Wallenberg Foundation (KAW).