Schedule and Information

  • Location: AAAI-22 Workshop.
  • Date: 28 February or 1 March 2022.
  • Paper Submission Deadline: 12 November 2021, 5:00:00 PM PST
  • Author Notification: 3 December 2021, 5:00:00 PM PST
  • Paper submissions: See more information below in CFP.
  • Contact: For any questions, please email rl4edorg AT
  • Updates:
    • 2021-10-15: If you are potentially interested in attending, please send an email to rl4edorg AT with your name/affiliation and we can add you to the invitee list.
    • 2021-10-15: Please refresh the page to ensure you have the latest content.


This workshop aims to bring together researchers and practitioners interested in the broad areas of reinforcement learning (RL) and education (ED). The workshop will focus on two thrusts:

  • Exploring how we can leverage recent advances in RL methods to improve state-of-the-art technology for ED.
  • Identifying unique challenges in ED that are beyond the current methodology, but can help nurture technical innovations and next breakthroughs in RL.
We welcome attendance from individuals who do not have something they'd like to submit but who are interested in RL4ED research. If you are potentially interested in attending the workshop, please send an email to rl4edorg AT and we can add you to the invitee list.

Topics of Interest

Topics of interests in the workshop include (but are not limited to) the following:
Leveraging recent advances in RL methods for ED problem setings
  • Survey papers summarizing recent advances in RL with applicability to ED.
  • Developing toolkits, datasets, and challenges for applying RL methods to ED.
  • Using RL for online evaluation and A/B testing of different intervention strategies in ED.
  • Novel applications of RL for ED problem settings.
Unique challenges in ED problem settings for nuturing next breakthroughs in RL methods
  • Using pedagogical theories to narrow the policy space of RL methods.
  • Using RL methodology as a computational model of students in open-ended learning domains.
  • Developing novel offline RL methods that can efficiently leverage historical student data.
  • Combining statistical power of RL with symbolic reasoning to ensure the robustness for ED.

Call for Papers

We solicit submissions of two types:
  • Research track papers reporting the results of ongoing or new research, which have not been published before. In particular, we encourage papers covering late-breaking results and work-in-progress research. Submissions should follow the AAAI'22 format and are encouraged to be up to four pages, excluding references and appendices. Papers submitted for review do not need to be anonymized. There will be no official proceedings, but the accepted papers will be made available on the workshop website. Accepted papers will be either presented as a talk or poster.
  • Encore track papers that have been recently published, or accepted for publication in a conference or journal. For this track, authors only need to submit the Title and Abstract of their paper to the submission site, and no PDF needs to be uploaded. At the end of the Abstract, authors should clearly state the venue where the paper was previously published and provide a URL link to access the PDF of the paper online. Accepted papers will be either presented as a talk or poster. This is a unique opportunity for the researchers to further broaden the dissemination and impact of their important work.

Please submit papers at