[agents] CFP:IJCAI 2021 Workshop on Robust and Reliable Autonomy in the Wild

[Sandhya Saisubramanian]

*Please help forward to interested parties*.



Call for Papers (CFP): Workshop on *Robust and Reliable Autonomy in the
Wild (R2AW) *at IJCAI 2021


Website: http://rbr.cs.umass.edu/r2aw/

Submission deadline: April 30, 2021 (AoE)

Submission link: https://easychair.org/conferences/?conf=r2aw

Contact:  R2AW.ijcai21 [at] gmail.com


===Workshop Overview===



The rapid development and deployment of autonomous systems in the open
world has highlighted the need for advances in the theory and practice of
robust and reliable AI. This workshop aims to bring together researchers
from academia and industry to discuss the challenges involved in deployed
autonomous systems, particularly systems that operate in the presence of
minor perturbations or noise in the environment, and under model
imprecision and uncertainty. The workshop will offer a forum for
researchers to discuss progress, identify knowledge gaps, and learn from
case studies in robust and reliable decision-making, drawing on a wide
range of methods, including automated planning, reinforcement learning,
decision-theory, formal verification, multi-agent systems, game theory,
robotics, AI ethics, and human factors. We welcome the participation of
researchers from different disciplines representing different perspectives
on the topic.



Relevant research challenges include (but are not limited to):

   - Definitions of safety, robustness, reliability, and resilience
   - Evaluation metrics for robustness and reliability, under model
   imprecision
   - Decision-making representations, models, and algorithms for the open
   world
   - Techniques to achieve resilient decision-making, under unmodelled
   disturbances
   - Techniques to recognize and avoid negative side effects of AI systems
   - Techniques for ethical, interpretable, fair, and trustworthy
   decision-making
   - Case studies of robustness and reliability in deployed autonomous
   systems
   - Learning to improve robustness and reliability from human feedback
   - Models and algorithms to support competence-aware autonomy



===Workshop Format and Submission Guidelines===



This is a one-day workshop that will include keynote invited speakers,
plenary presentations of submitted papers, poster sessions, and discussion
sessions. Accepted papers will be presented as posters or contributed oral
presentations. The workshop will have electronic, non-archival proceedings.

Submissions can be one of the following types:

   - Full technical paper (up to 8 pages)
   - Survey paper (up to 8 pages)
   - Case-studies describing the experiences with deployed systems (up to 8
   pages)
   - Short paper (up to 4 pages)
   - Position paper (up to 4 pages)



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.



There is no page limit for references and supplementary materials. Authors
should rely on the supplementary material only to include details that do
not fit in the main paper. Submissions should be in PDF and formatted
according to IJCAI 2021 guidelines <https://www.ijcai.org/authors_kit>.
Papers accepted or under review at other conferences can be submitted and
presented at the workshop, subject to the conference guidelines.



Submission link:  https://easychair.org/conferences/?conf=r2aw

Contact: R2AW.ijcai21 [at] gmail.com



===Important Dates===

Paper submission: April 30, 2021 (AoE)

Author notification: May 25, 2021

Camera-ready submission: TBD


===Invited Speakers===

   - Tom Dietterich, Oregon State University
   - Anca Dragan, UC Berkeley


===Organizers===

   - Nick Hawes <https://www.robots.ox.ac.uk/~nickh/>, University of Oxford
   - Ece Kamar <https://www.ecekamar.com/>, Microsoft Research
   - Bruno Lacerda <https://ori.ox.ac.uk/people/bruno-lacerda/> (Co-chair),
   University of Oxford
   - Sandhya Saisubramanian <https://www.sandhyasai.com/> (Co-chair),
   University of Massachusetts Amherst
   - Shlomo Zilberstein <https://groups.cs.umass.edu/shlomo/>, University
   of Massachusetts Amherst



===Program Committee===

   - Alessandro Abate, University of Oxford
   - David Abel, DeepMind
   - Ignacio Alvarez, Intel Labs, USA
   - Tapomayukh "Tapo" Bhattacharjee, Cornell University
   - Joydeep Biswas, University of Texas, Austin
   - Mathias Bürger, Bosch Center for Artificial Intelligence
   - Xiaoping Chen, University of Science and Technology of China
   - Tesca Fitzgerald, Carnegie Mellon University
   - Igor Gilitschenski, MIT
   - Dylan Hadfield-Mennel, UC Berkeley
   - Christoffer Heckman, University of Colorado, Boulder
   - Erez Karpas, Technion
   - Sarah Keren, Harvard University, Hebrew University
   - Mykel Kochenderfer, Stanford University
   - Jana Koehler, Saarland University
   - Masoumeh Mansouri, University of Birmingham
   - Sheila McIlraith, University of Toronto
   - Abdel-Illah Mouaddib, University of Caen Basse-Normandie
   - David Parker, University of Birmingham
   - Marek Petrik, University of New Hampshire
   - Ramya Ramakrishnan, ASAPP Inc.
   - Matthijs Spaan, Delft University of Technology
   - Florent Teichteil-Koenigsbuch, Airbus AI Research
   - Pratap Tokekar, University of Maryland
   - Vaibhav Unhelkar, Rice University





Best,

Sandhya
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