Joint Workshop on Planning for Complex Real-World Applications (CAIPI) and Bridging the Gap Between AI Planning and (Reinforcement) Learning (PRL)
IJCAI’26
Bremen, Germany
Date: August 15 - 17, 2026
prl.theworkshop@gmail.com \
Aim and Scope
Symbolic planning, Reinforcement Learning, and emerging directions such as LLMs for planning and Neuro-Symbolic approaches all contribute important theoretical and applied perspectives on sequential decision-making. However, these communities often evolve in parallel, with distinct assumptions, theoretical backbones, methods, benchmarks, and forms of evaluation. As a result, progress on planning is fragmented across community boundaries, despite a shared interest in solving complex decision-making problems.
This joint workshop aims to bring these communities together across both dimensions of the field: theoretical foundations and applications. It provides a platform for researchers working on symbolic, learning-based, and hybrid planning approaches to discuss common challenges, compare methodologies, and identify opportunities for integration. By fostering exchange across established and emerging research directions, the workshop seeks to strengthen connections within the broader planning community and support the development of more general and practically relevant planning approaches.
Topics of Interest
We invite submissions at the intersection of AI Planning and (Reinforcement) Learning for theoretical and applied problems. The topics of interest include, but are not limited to, the following
- Novel real-world applications for planning and reinforcement learning
- Novel planning algorithms for real-world applications
- Usage of Large Language Models (LLMs) in planning and reinforcement learning
- Automated generation of planning domain descriptions
- Reinforcement learning (model-based, Bayesian, deep, hierarchical, etc.)
- Learning for planning (L4P)
- Generalized planning
- Monte Carlo planning
- Model representation
- Model learning
- Planning using approximated/uncertain (learned) models
- Learning search heuristics for planner guidance
- Theoretical aspects of planning and reinforcement learning
- Dataset and Benchmarks across planning and RL
- Action policy analysis or certification
- Reinforcement learning and planning competition(s)
Important Dates
- Paper submission deadline: May 15, AOE
- Paper acceptance notification: June 15, AOE
IJCAI will be in-person this year. Authors of accepted workshop papers are expected to physically attend the conference and present in person.
Submission Details
We solicit workshop paper submissions relevant to the above call of the following types:
- Long papers – 10 - 15 pages + unlimited references / appendices
- Short papers – 6 - 9 pages + unlimited references / appendices
- Extended abstracts – up to 4 pages + unlimited references/appendices
We aim to publish the workshop proceedings through CEUR-WS (https: //ceur-ws.org/). This is optional, meaning accepted submissions can choose to be part of the proceedings but don’t have to. Please note that CEUR-WS workshop proceedings are archival. The Latex template can be found here, with more information available here.
Authors submitting papers rejected from other conferences, please ensure you do your utmost to address the comments given by the reviewers. Please do not submit papers that are already accepted for the IJCAI-ECAI main conference to the workshop. You may submit already accepted papers from other conferences if they fit the workshop’s scope. If you submit an already accepted paper, the paper cannot be included in the CEUR-WS workshop proceedings.
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 submission will be available soon.
We do not insist on papers being submitted anonymously initially; this decision is left to the discretion of the author. If a paper is simultaneously being considered at a venue where anonymity is required, you have the option to submit it without author details, considering the possibility of a shared reviewer pool.
Organizing Committee
- Forest Agostinelli, University of South Carolina, Columbia, USA.
- Zlatan Ajanović, RWTH Aachen University, Aachen, Germany.
- Dillon Ze Chen, Laboratory for Analysis and Architecture of Systems (LAAS-CNRS), Toulouse, France.
- Jonas Erhardt, Helmut-Schmidt-University, Hamburg, Germany.
- Alexander Diedrich, Helmut-Schmidt-University, Hamburg, Germany.
- Timo P. Gros, German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany.
- René Heesch, Helmut-Schmidt-University, Hamburg, Germany.
- Andrea Micheli, Fondazione Bruno Kessler, Trento, Italy.
- Oliver Niggemann, Helmut-Schmidt-University, Hamburg, Germany.
- Shahaf S. Shperberg, Ben-Gurion University, Be’er Sheva, Israel.
- Ayal Taitler, Ben-Gurion University, Be’er Sheva, Israel.
- Niklas Widulle, Helmut-Schmidt-University, Hamburg, Germany.
Please send your inquiries to prl.theworkshop@gmail.com