International Planning Competition (IPC) 2023: Probabilistic and Reinforcement Learning Track
Call for Participations and domains
As part of the International Conference on Planning and Scheduling (ICAPS) 2023 in Prague, we will be hosting a novel Planning and Reinforcement Learning (RL) track. Key features and goals of the competition include:
Critically, as a differentiator from other RL competitions, the full RDDL declarative model will be available to competitors to use (if they want). With this we hope to encourage the RL community to think about how they can leverage explicit model knowledge when available. Furthermore, we hope to see pure RL, pure planning, and hybrid approaches competing in order to obtain a head-to-head comparison of these different methodologies.
We invite interested competitors to join the competition discussion:
We also invite RDDL domain contributions from the community. If you are interested in designing a domain for the competition, please contact us at the above discussion list as soon as possible. If your domain suggestion is chosen for the competition, we will work with you to design and adapt the domain to suit the competition. More information on the competition and the pyRDDLGym infrastructure can be found at
which includes a description of the RDDL modeling language as well as the Python RDDLGym interface and quick install instructions for running the existing sample domains including
If you have any questions about the competition or participation, please do not hesitate to reach out to us.
Ayal Taitler and Scott Sanner (University of Toronto)