Full papers
Original research contributions with comprehensive experiments and analysis.
Machine Learning/CORE Unranked
Continual RL @ RLC 2026
Continual Reinforcement Learning Workshop at RLC 2026
The Continual RL @ RLC 2026 workshop focuses on continual reinforcement learning, bringing together researchers to present and discuss novel methods, benchmarks, and applications that enable agents to learn continuously over time without forgetting past tasks. It is affiliated with the Reinforcement Learning Conference (RLC) 2026.
Key deadlines
Verified September 9, 2026Full paper
May 30, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
May 30, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short papers
Preliminary results, novel ideas, or focused case studies with concise presentation.
Work-in-progress
Ongoing research with early results or open problems for discussion.
Research areas in scope
01
Topics
Continual learning in reinforcement learningCatastrophic forgetting in RLLifelong policy adaptationSample efficiency in continual RLBenchmarking continual RL algorithmsTransfer and meta-learning for continual RLExploration in non-stationary environmentsRepresentation learning for continual RLSafety and stability in continual RLReal-world applications of continual RL
Policies worth checking twice
- Submissions must be anonymized for double-blind review.
- Papers must not exceed 8 pages (excluding references).
- Dual submission to other conferences or journals is not allowed during review.
- Author lists and affiliations cannot be changed after the submission deadline.
- Authors must include an AI-use statement describing any generative AI tools used in the research.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026