ICAPS 2017 Planning and Learning Track
Call for Papers
In 2017, ICAPS will run a Planning and Learning track as part of the main conference. Machine learning has impacted all aspects of Artificial Intelligence and Computer Science, and planning is no exception. Indeed, the planning and scheduling community have a long history of incorporating learning machinery into planning systems as well as deploying planning systems for learning. This new track provides an opportunity for the AI planning and scheduling community to engage directly with developments in the learning community for the benefits of both.
The Planning and Learning track aims to present research at the intersection of the fields of machine learning and planning & 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:
- Reinforcement learning;
- Learning to improve the effectiveness of planning systems;
- Learning domain models;
- Planning in learned domain models;
- Learning effective heuristics and other forms of control knowledge;
- Planning applied to automating machine learning systems;
- Applications that involve a combination of learning and planning
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.
All papers, regardless of length, will be reviewed against the standard criteria of relevance, originality, significance, clarity and soundness, and are expected to meet the same high standards set by ICAPS. Short papers may be of narrower scope, for example by addressing a highly specific issue, or proposing or evaluating a small, yet important, extension of previous work or new idea.
Authors making multiple submissions must ensure that each submission has significant unique content. Papers submitted to ICAPS 2017 may not be submitted to other conferences or journals during the ICAPS 2017 review period nor may they be already under review or published in other conferences or journals. Overlength papers will be rejected without review.
All submissions will be made electronically, through the EasyChair conference system: https://www.easychair.org/conferences/?conf=icaps2017. Submissions must be in the AAAI format. For more information, see the submission instructions on ICAPS 2017 submission page.
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: http://www.aaai.org/Publications/Author/author.php
In addition to the submitted PDF paper, authors can additionally 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).
- 18 November 2016 - Abstracts (electronic submission) due
- 22 November 2016 - Papers (electronic submission, PDF) due
- 26 January 2017 - Notification of acceptance
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!
Planning and Learning Track chairs:
- Alan Fern (Oregon State)
- Michael Littman (Brown University)
Please direct any question to Alan.Fern@oregonstate.edu.