May 10th, 2022 
Daniela Lopez de Luise
CALL FOR PAPERS
Bridging the Gap Between AI Planning and Reinforcement Learning
(PRL 2022)
https://prl-theworkshop.github.io/prl2022-ijcai/
IJCAI 2022, Vienna – July 23-25, 2022.
IMPORTANT: IJCAI will be in-person this year. Authors of accepted workshop papers
are therefore expected to physically attend the conference and present in person.
The submission website is now open:
https://easychair.org/my/conference?conf=prl20220
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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.
Workshop topics:
================
The workshop solicits work at the intersection of the fields of reinforcement
learning and planning. One example is so-called goal-directed reinforcement
learning, where a goal must be achieved, and no partial credit is given for
getting closer to the goal. In this case, a usual metric is success rate. 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:
* Theoretical aspects of planning and reinforcement learning
* Goal-oriented sequential decision methods combining planning, RL
or other ML methods.
* Goal-directed reinforcement learning (model-based, Bayesian, deep, etc.)
* Safe Reinforcement Learning and Planning
* Certification/analysis of learned policies/models
* Neuro-symbolic methods for RL
* Hierarchical RL and symbolic abstractions
* Compositional RL and symbolic methods
* Planning using approximated/uncertain (learned) models
* Monte Carlo Planning
* Applications of planning methods to RL
* Various levels of generalization (across goals, objects/domain, domains)
* Reinforcement Learning and planning competition(s)/benchmarks
Important Dates:
================
* Submission system opened: Friday, April 29th, 2022 (UTC-12 timezone)
* Submission deadline: Friday, May 13th, 2022 (UTC-12 timezone)
* Notification date: Friday, June 3rd, 2022
* Camera-ready deadline: Friday, June 17th, 2022
* Workshop date: July 23-25 (TBD), 2022
Submission Procedure:
=====================
We solicit workshop paper submissions relevant to the above call of the
following types:
* Long papers — up to 8 pages + unlimited references / appendices
* Short papers — up to 4 pages + unlimited references / appendices
* Extended abstracts — up to 2 pages + unlimited references / appendices
Please format submissions in AAAI style (see instructions in the Author Kit at
https://www.aaai.org/Publications/Templates/AuthorKit22.zip). Authors considering
submitting to the workshop papers rejected from other conferences, please ensure
you do your utmost to address the comments given by the reviewers.
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, preliminary work, position papers or challenges that
might help bridge the gap.
As the main purpose of this workshop is to solicit discussion, the authors are
invited to use the appendix of their submissions for that purpose.
Paper submissions should be made through EasyChair:
https://easychair.org/my/conference?conf=prl20220
Workshop Organizers
=====================
Michael Katz, IBM T.J. Watson Research Center, NY, USA
Hector Palacios, ServiceNow Research, Montreal, Canada
Vicenç Gómez, Universitat Pompeu Fabra, Barcelona, Spain
Please send your inquiries to prl.theworkshop@gmail.com
