Long papers
Up to 8 pages + unlimited references / appendices
AI/CORE Unranked
CAIPI & PRL @ IJCAI-ECAI 2026
Joint Workshop CAIPI and PRL at IJCAI-ECAI 2026
The CAIPI & PRL workshop at IJCAI-ECAI 2026 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 encourages submissions that explore intersections between these fields, including model learning, heuristic search, and applications in complex domains.
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
Research Topics
Reinforcement learning (model-based, Bayesian, deep, etc.)Model representation and learning for planningPlanning using approximated/uncertain (learned) modelsMonte Carlo planningLearning search heuristics for planner guidanceTheoretical aspects of planning and reinforcement learningReinforcement Learning and planning competition(s)Multi-agent planning and learningApplications of both reinforcement learning and planning
Policies worth checking twice
- Submissions must be formatted in AAAI style
- Papers must not exceed 9 pages including references
- Papers already accepted for the main ICAPS conference cannot be submitted to the workshop
- Authors are encouraged to address reviewer comments if submitting previously rejected papers
- Extended abstracts may summarize published work, preliminary results, position papers, or challenges
- Appendices may be used to facilitate discussion
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026