We are the Representation, Learning and Planning Lab at Linköping University, Sweden. Our research topics include:
- Learning representations for planning
- Planning models, algorithms, and techniques
- Planning and reinforcement learning
- Generalized planning
- Model-based vs. model-free intelligence
You can find us in the E building close to entrance 29C.
- 2023-05-25: Our WASP Industrial PhD project Neuro-Symbolic AI for Improving Energy Efficiency in 6G has been accepted.
- 2023-05-19: Our group has three accepted papers at KR 2023.
- 2023-04-01: Our project Symbolic Search for Diverse Plans and Maximum Utility for the AIPlan4EU project open call for innovators has been accepted.
- 2023-03-30: Our WASP PhD project Collaborative Constraint-Based Planning has been accepted.
- 2023-03-01: Mauricio Salerno is visiting our group for three months.
- 2023-02-06: Our group has four accepted papers at ICAPS 2023.
- 2022-11-18: Our group has one accepted paper at AAAI 2023.
- 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.
- 2022-10-17: Martin Funkquist joins the group.
- 2022-10-13: Jendrik Seipp receives a Zenith project grant from the Faculty of Science and Engineering at Linköping University.
- 2022-10-01: Markus Fritzsche and Mika Skjelnes join the group.
- 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).