While AI Planning and Reinforcement Learning communities focus on similar sequential decision-making problems, these communities remain somewhat unaware of each other on specific problems, techniques, methodologies, and evaluation.
This workshop aims to encourage discussion and collaboration between the researchers in the fields of AI planning and reinforcement learning. We aim to bridge the gap between the two communities, facilitate the discussion of differences and similarities in existing techniques, and encourage collaboration across the fields. We solicit interest from AI researchers that work in the intersection of planning and reinforcement learning, in particular, those that focus on intelligent decision making. As such, the joint workshop program is an excellent opportunity to gather a large and diverse group of interested researchers.
The workshop solicits work at the intersection of the fields of reinforcement learning and planning. We also solicit work solely in one area that can influence advances in the other so long as the connections are clearly articulated in the submission.
Submissions are invited for topics on, but not limited to:
We solicit workshop paper submissions relevant to the above call of the following types:
Please format submissions in AAAI style (see instructions in the Author Kit 2021 at AAAI).
Some accepted long papers will be accepted as contributed talks. All accepted long and short papers and extended abstracts will be given a slot in the poster presentation session. Extended abstracts are intended as brief summaries of already published papers (a reference to the publication is expected), preliminary work, position papers or challenges that might help bridge the gap.
Paper submissions should be made through EasyChair, https://easychair.org/conferences/?conf=prl2021.
Please send your inquiries by email to the organizers at email@example.com.
For up-to-date information, please visit the PRL website, https://prl-theworkshop.github.io.