ICAPS 2023 Call for Papers: Planning and Learning Track

The Planning and Learning track aims to present research at the intersection of the fields of machine and reinforcement learning with planning and scheduling. In particular, we are interested in work that draws substantially from the objectives, techniques, or methodologies of both fields.

Topics include, but are not limited to the following:

  • Reinforcement learning using planning (model-based, Bayesian, deep, etc.)
  • Learning domain and action models for planning
  • Representations for learned models in planning
  • Learning effective heuristics and other forms of planning control knowledge
  • Theoretical aspects of planning and learning
  • Multi-agent planning and learning
  • Planning applied to automating machine learning systems
  • Learning to improve the effectiveness of planning & scheduling systems
  • Applications that involve a combination of learning with planning or scheduling

Please note: papers that do not clearly make a case for their relevance to model-based planning techniques or that do not compare to model-based planning techniques may be rejected without review.

Author Guidelines

Authors may submit long papers (8 pages plus up to one page of references) or short papers (4 pages plus up to one page of references). The type of paper must be indicated at submission time. Both long and short papers will be reviewed against the standard criteria of relevance, originality, significance, clarity and soundness, and are expected to meet the high standards set by ICAPS. Short papers may be of narrower scope. For example, they can either address a highly specific issue, or propose/evaluate a small, yet important, extension of previous work or a new idea.

Authors making multiple submissions must ensure that each submission has significant unique content. Papers submitted to ICAPS 2023 may not be submitted to other conferences or journals during the ICAPS 2023 review period, nor may be already under review or published in other conferences or journals. Over-length papers will be rejected without review.

Ethical/Societal Impact

It is optional for authors to include a statement of the potential broader impact of their work, including its ethical aspects and future societal consequences. This statement can be included in either the main body pages or the reference page. If such a statement is not included in the paper but the reviewers deem that such a statement is necessary, then the authors will be asked to provide one during the author response period for review. If the paper is accepted, the statement provided will need to be incorporated in the camera-ready version.

Submission Instructions

All submissions will be made electronically, through the EasyChair conference system. Submitted PDF papers should be anonymous for double-blind reviewing, adhere to the page limits of the relevant track CFP/submission type (long or short), and follow the AAAI author kit instructions for formatting.

In addition to the submitted PDF paper, authors can submit supplementary material (videos, technical proofs, additional experimental results) for their paper. Please make sure that the supporting material is also anonymized. Papers should be self-contained; reviewers are encouraged, but not obligated, to consider supporting material in their decision.

The proceedings will be published by AAAI Press. All accepted papers will be published in the main conference proceedings and will be presented orally at the conference (full papers will be allocated more time).

Important Dates

We have arranged our schedule to allow for the revision and resubmission of papers rejected from AAAI 2023.

  • November 25, 2022 - Abstracts due (electronic submission)
  • November 30, 2022 - Full papers due (electronic submission, PDF)
  • January 16-19, 2023 - Author feedback period
  • February 4, 2023 - Notification of acceptance or rejection

The reference timezone for all deadlines is UTC-12. That is, as long as there is still some place anywhere in the world where the deadline has not yet passed, you are on time!

ICAPS 2023 Planning and Learning Track Chairs

  • Alan Fern, Oregon State University, USA
  • Eva Onaindia, UPV, Spain

For inquiries contact: icaps23.learning@easychair.org