Long papers
Up to 8 pages + unlimited references / appendices
Machine Learning/CORE Unranked
PRL ICAPS 2026
Tenth Workshop on Bridging the Gap Between AI Planning and (Reinforcement) Learning (PRL)
The PRL @ ICAPS 2026 workshop aims to bridge the gap between AI planning and reinforcement learning communities by fostering collaboration and discussion on shared challenges in sequential decision-making. It is the tenth edition of the PRL workshop series, focusing on intersections such as learning for planning, model-based RL, and neuro-symbolic methods, while coordinating with related workshops like RIPL and LM4Plan.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short papers
Up to 4 pages + unlimited references / appendices
Extended abstracts
Up to 2 pages + unlimited references/appendices
Research areas in scope
01
Topics of Interest
Reinforcement learning (model-based, Bayesian, deep, hierarchical, etc.)Learning for planning (L4P)Generalized planningMonte Carlo planningModel representationModel learningPlanning using approximated/uncertain (learned) modelsLearning search heuristics for planner guidanceTheoretical aspects of planning and reinforcement learningDataset and Benchmarks across planning and RLAction policy analysis or certificationReinforcement learning and planning competition(s)Multi-agent planning and learningApplications of both (reinforcement) learning and planning
Policies worth checking twice
- Authors of accepted workshop papers are expected to physically attend the conference and present in person.
- Do not submit papers that are already accepted for the main ICAPS conference to the workshop.
- You may submit already accepted papers from other conferences if they fit the workshop’s scope.
- Papers are non-archival.
- Paper submissions should be made through OpenReview.
- Anonymity is not required initially; authors may choose whether to submit anonymously.
- Upon acceptance, papers will be publicly posted on the PRL website with full author information.
- Extended abstracts are intended as brief summaries of already published papers, preliminary work, position papers, or challenges.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026