Poster
All accepted papers will be presented as posters; posters must be 3 ft by 4 ft in portrait orientation.
Machine Learning/CORE Unranked
RL in Big Worlds 2026
Reinforcement Learning in Big Worlds Workshop at RLC 2026
The RL in Big Worlds 2026 workshop explores reinforcement learning in environments where agents face infinite, unforeseeable possibilities and must adapt continuously with limited resources. It challenges the assumption that agents can rely on finite, fully observable, or deterministic environments, instead promoting research on continual learning, predictive representations, and algorithms that operate under real-world constraints.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Oral Presentation
One paper will be selected for a 15-minute oral presentation.
Research areas in scope
01
Research Topics
Methods that learn to construct an agent state from the history of observations and actionsMethods for exploration that operate on the agent state instead of the environment's stateProposals and benchmarks for evaluating algorithms in big worlds (e.g., limiting computation or memory)Methods for continual learning to deal with unforeseeable situations (e.g., preventing catastrophic forgetting)Methods for learning models of the agent state and planning with approximate modelsMethods for discovering temporal abstractions and using them for exploration and planningMeta-learning methods that learn aspects of the learning algorithm (e.g., online hyperparameter adaptation)Theory that makes assumptions about the agent's capabilities but not about the environment's complexity
Policies worth checking twice
- Papers must be anonymized for submission.
- Submissions must be in PDF format using the RLC style file.
- Paper length must be 4 to 8 pages, excluding references.
- No cover page is needed.
- Recently published work (after September 2024) may be submitted.
- Submissions are not archival.
- Double submission of the same paper to another RLC workshop is not allowed.
- The review process is double-blind.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026