[NeurIPS 2022] CFP^2: Call for Papers and Call for Panels: Reinforcement Learning for Real Life Workshop @ NeurIPS 2022
Yuxi Li
On behalf of the workshop organizing committee and MLJ SI guest editors:
Emma Brunskill (Stanford)
Minmin Chen (Google)
Omer Gottesman (Brown U.)
Lihong Li (Amazon)
Yuxi Li (Attain.ai)
Yao Liu (ByteDance)
Zongqing Lu (PKU)
Niranjani Prasad (Microsoft)
Zhiwei (Tony) Qin (Lyft)
Csaba Szepesvari (Deepmind & U. of Alberta)
Matthew E. Taylor (U. of Alberta)
Reinforcement learning (RL) is a general learning, predicting, and decision-making paradigm and applies broadly in many disciplines in science, engineering, and the arts. RL has seen prominent successes in many problems, such as those in simulated environments like Atari games and AlphaGo, and those in real life like robotics, recommender systems, and nuclear fusion. However, given the significant theoretical and algorithmic gains made in the past few years, applying RL in real life remains challenging, and a natural question is:
Why isn’t RL used even more often and how can we improve this?
The main goals of the workshop are to: (1) identify key research problems that are critical for the success of real-world applications; (2) report progress on addressing these critical issues; and (3) have practitioners share their success stories of applying RL to real-world problems, and the insights gained from such applications.
We invite paper submissions of original work successfully applying RL algorithms to real-life problems and/or addressing practically relevant RL issues. Our topics of interest are general, w.r.t. practical RL algorithms, practical issues, and applications.
Topics of interest include (but are not limited to):
+ studies about real-life RL systems, esp. about deployment/product
+ significant efforts for a high-fidelity simulator, esp. for a complicated system
+ significant efforts for benchmarks/datasets
+ significant efforts for human factors
The following alone is not considered real-life RL:
- practical work with existing simulator/benchmark/dataset only, w/o significant real-life efforts
- theory/algorithm work with toy/simple experiments only, w/o significant real-life efforts
Paper Submission
Deadline: Sep. 15, 2022
Notification: Oct. 15, 2022
We invite unpublished submissions up to 9 pages excluding references and appendix, in PDF format using the NeurIPS 2022 template and style guidelines. Here is a customized style file for the workshop. (In the .tex file, use "\usepackage{neurips_2022}" for the submission, and use "\usepackage[final]{neurips_2022}" for the final version if accepted.) The paper review process will be single-blind. All accepted papers will be presented as posters, some as spotlight talks, and all will be made available on the workshop website. Accepted papers are non-archival, i.e. there will be no proceedings for this workshop. Selected papers will be further considered for the Machine Learning Journal Special Issue on Reinforcement Learning for Real Life.
https://cmt3.research.microsoft.com/RL4RealLife2022/ (Choose “Papers”)
We invite proposals for panel discussions at the Reinforcement Learning for Real Life (RL4RealLife) Workshop @ NeurIPS 2022.
The proposed panel should be informative and engaging. We expect selected panels to address novel, aspiring, and open questions of broad interest to the RL4RealLife community. Each panel is a 60-minute session. We encourage fully in-person panels, and consider virtual ones as well.
A panel proposal must include:
+ A title and a description of the content. (two pages)
* Why is the topic of interest to the RL4RealLife community?
* What are possible perspectives that might spark discussions?
* Who are the panelists? Who has been confirmed?
* What are the likely positions of the panelists on the topic?
* What are the potential questions to facilitate discussions?
* How will the audience be involved in the discussions?
+ An account of the efforts made to ensure diversity of the chair(s) and panelists.
+A very brief advertisement or tagline for the panel discussion, up to 140 characters, that highlights any key information you wish prospective attendees to know. Please input this as the abstract.
+ Name, affiliation, brief bios, and contact info for one or two chairs/moderators of the proposed panel. (no page limit)
+ Names, affiliations, and brief bios for up to 5 confirmed panelists. (no page limit)
The proposal is submitted as a single PDF file.
We will follow the Guidance for NeurIPS Workshop Proposals 2022, https://blog.neurips.cc/2022/04/24/guidance-for-neurips-workshop-proposals-2022/.
Our Call for Panels borrows ideas from https://vldb.org/2022/?call-for-panels and https://chi2022.acm.org/for-authors/interacting-and-discussing/panels/. We encourage potential panel organizers to refer to them.
Deadline: Aug. 30, 2022
Notification: Sep. 15, 2022
https://cmt3.research.microsoft.com/RL4RealLife2022/ (Choose “Panel Proposals”)
We plan to organize 2 panels by us workshop co-chairs:
Panel: RL Theory-Practice Gap. Moderator: Emma Brunskill
Panel: RL Benchmarks. Moderator: Minmin Chen