[CFP] AAMAS Workshop on Rebellion and Disobedience in AI (RaD-AI)

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Reuth Mirsky

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Jan 5, 2022, 12:08:53 PMJan 5
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Dear Colleagues,

We invite you to submit your work to the Rebellion and Disobedience in AI (RaD-AI) workshop as part of AAMAS 2022. 


Most existing research on collaborative robots and agents, assume that a “good” agent is one that complies with the commands it is given and works in a predictable manner under the consent of the human it serves. The goal of this workshop is to challenge this assumption and to rethink the desired abilities and responsibilities of collaborative agents: 

When and how should an artificial agent rebel or otherwise disobey? 

We invite the participation of researchers interested in directly addressing Rebellion and Disobedience in AI (RaD-AI) agents, as well as submissions on RaD-AI and related topics relevant for designing, developing, demonstrating, or evaluating RaD-AI agents, including but not limited to:

- Plan recognition

- Goal reasoning

- Value alignment

- Human-agent interaction

 
Paper Submissions:

Papers should be submitted through easychair: https://easychair.org/conferences/?conf=radai22

Submission deadline is January 30, 2022. 

Notifications will be sent by February 27, 2022.

We accept submissions of the following types: regular research papers (up to 6 pages), position papers (up to 2 pages), and tool talks (up to 2 pages).

Papers must be in high-resolution PDF format, formatted for US Letter (8.5" x 11") paper, using Type 1 or TrueType fonts. Reviews are double-blind, and submissions must conform to the AAMAS-22 submission instructions found here: https://aamas2022-conference.auckland.ac.nz/calls/submission-instruction/


Organizing Committee:
David Aha, Navy Center for Applied Research in AI, Naval Research Laboratory
Reuth Mirsky, Computer Science Department, Bar Ilan University (reu...@gmail.com)
Peter Stone, Computer Science Department, The University of Texas at Austin


Reuth Mirsky

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Jan 31, 2022, 11:09:47 AMJan 31
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Dear Colleagues,

We invite you to submit your work to the Rebellion and Disobedience in AI (RaD-AI) workshop as part of AAMAS 2022. Please notice the extended submission deadline.


Most existing research on collaborative robots and agents, assume that a “good” agent is one that complies with the commands it is given and works in a predictable manner under the consent of the human it serves. The goal of this workshop is to challenge this assumption and to rethink the desired abilities and responsibilities of collaborative agents: 

When and how should an artificial agent rebel or otherwise disobey? 

We invite the participation of researchers interested in directly addressing Rebellion and Disobedience in AI (RaD-AI) agents, as well as submissions on RaD-AI and related topics relevant for designing, developing, demonstrating, or evaluating RaD-AI agents, including but not limited to:

- Plan recognition
- Goal reasoning
- Value alignment
- Human-agent interaction
 
Paper Submissions:
Papers should be submitted through easychair: https://easychair.org/conferences/?conf=radai22

Submission deadline is January 30, 2022, February 7, 2022.

Reuth Mirsky

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Apr 28, 2022, 5:25:38 PMApr 28
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Dear Colleagues,

We invite you to join the Rebellion and Disobedience in AI (RaD-AI) workshop as part of AAMAS 2022. 

Details:
The workshop will be online, and will take place on May 9, 2022. It will be split into two sessions to enable participants from around the world to join. The full schedule is available here: https://sites.google.com/view/rad-ai/schedule

RSVP:
This year, attending the AAMAS workshops is free of charge.
However, to help us monitor the expected attendance and to share more relevant information with you closer to the workshop, please RSVP using this form: https://forms.gle/5ccpFvFGmVmkggZDA
If you do plan on attending additional parts of AAMAS, please don’t forget to register here: https://aamas2022-conference.auckland.ac.nz/attending/registration/

We look forward to seeing you at RaD-AI!

Organizing Committee:
David Aha, Navy Center for Applied Research in AI, Naval Research Laboratory
Reuth Mirsky, Computer Science Department, Bar Ilan University (reu...@gmail.com)
Peter Stone, Computer Science Department, The University of Texas at Austin
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