[robotics-worldwide] [CFP] [Meetings]: FINAL CFP AAAI Symposium on Educational Advances in AI 2017---Robotics track!

Jim Boerkoel boerkoel at cs.hmc.edu
Sun Sep 11 10:12:21 PDT 2016


Please note the special track on widely-accessible AI robotics tasks.
General call for Educational Advances in AI follows.

*The Seventh Symposium on Educational Advances in Artificial Intelligence
2017 (EAAI-17)*
*Call for Contributions: The 2017 NSG Robotics Challenge*
*February 5-6, 2017*
*San Francisco, California, USA (collocated with AAAI-17)*
Sponsored by the Association for the Advancement of Artificial Intelligence

Sharing AI Robotics curricula is difficult – but tantalizingly so!

Despite and because of this difficulty, EAAI wants to support the
development/sharing of compelling AI robotics curricula. The 2017 EAAI
NSG* AI-Robotics
challenge invites teams to create, prototype, and share a compelling,
accessible, and adaptable AI robotics task of their own design.

In a sense, this is a meta-robotics challenge, in which you are invited to
share a novel or adapted AI robotics challenge that maximizes both
curricular worth and easy deployment. Entries will have the opportunity to
be presented at EAAI (eaai.stanford.edu).

*(*Whereas DARPA has its "grand challenges," ours may seem not-so-grand –
but they're at least as challenging!)*

*Important Dates*

   - September 14, 2016: Author registration and electronic assignment
   submission deadline
   - November 9, 2016: Author notification of acceptance or rejection
   - November 28, 2016: Final assignment abstract and assignment revisions
   - February 5-6, 2016: EAAI-17


Directly supporting EAAI's principal focus – adaptable, effective resources
for AI education – the 2017 NSG challenge invites *creating an accessible
curricular module that engages students in both AI and robotics*. In a
sense, this is a meta-robotics challenge, in which you are invited to
create an AI robotics task that maximizes both curricular value and ease of

There are no constraints on the hardware, software, or curricular content
of the tasks submitted: *every *choice will confront tradeoffs relative to
the judging criteria noted below. All target educational levels and all
possible team compositions are invited: students, educators, researchers,

In keeping with EAAI's focus, this challenge especially targets
*undergraduate-level* tasks and curricular goals in particular. NSG
submissions targeting other audiences are welcome, too: they will be
considered in their own category. Furthermore, in the spirit of supporting
the undergraduate experience, we encourage submissions by undergraduate
students and faculty, working together as a team of equal contributors.

Additional details are available at www.cs.hmc.edu/~dodds/nsgc17/.


A submission to the NSG Challenge consists of two parts, a report and a

   -  a written report, describing the proposed task, including sections on
      - the "challenge" task itself, as well as the student audience it is
      meant for
      - the hardware and software required to tackle the challenge
      - the AI and programming skills the challenge elicits and reinforces
      - the experiences of the authors in trying out the challenge -- or in
      others'  trials of it
   - a presentation, made by one or more team members at EAAI
      - a 10-minute overview interlacing the challenge itself and its
      motivation, the materials and background needed, the AI content
      and the insights gained from the one or more trial runs
      - the 10-minute overview can (and ideally should) include videos that
      document at least one end-to-end execution of the challenge

These deliverables are deliberately open-ended: we welcome all ideas! Note
that these are essentially curricular submissions – *not robotics systems* per
se. This challenge is at heart pedagogical/curricular, not technological or

EAAI will archive all submissions for educators to adopt/adapt in the


There will be at least three judges who review all of the submissions. They
will rate each of the proposed robot curricular tasks by asking the
following questions. For each of these criteria, more would be better:

   - How well-pitched is the learning curve for the intended audience of
   - How well and how deeply is AI integrated into the students'
   contributions to the project?
   - How accessible is this project for other educators and institutions to
   adopt or adapt?
   - How open-ended, especially in terms of AI content and application, is
   the challenge?
   - How compelling would this challenge be for a wide audience of the
   intended ages, that is, how little specialized background is needed, in
   terms of hardware/software/languages/libraries?
   - How well does the submission incorporate software and tools widely
   used in the professional AI/robotics communities?
   - How much value-added can students contribute to the task's starting
   - How much sophistication and freedom, both in sensing and in processing
   sensor data, does the challenge make available for student exploration and


*Wait! These criteria are mutually contradictory. It's impossible to meet
all of them!*

*Yes.*  Welcome to the challenge!


*The Seventh Symposium on Educational Advances in Artificial Intelligence
2017 (EAAI-17)*

*Call for Papers*

*February 5-6, 2017*

*San Francisco, California, USA (collocated with AAAI-17)*

Sponsored by the Association for the Advancement of Artificial Intelligence


*Important Dates*

   - September 14, 2016: Paper submission deadline
   - November 9, 2016: Author notification of acceptance or rejection
   - November 28, 2016: Camera-ready copy due at the AAAI office
   - February 5-6, 2016: EAAI-17

EAAI-17 provides a venue for researchers and educators to discuss
pedagogical issues and share resources related to teaching and using AI in
education across a variety of curricular levels (K-12 through postgraduate
training), with an emphasis on undergraduate and graduate teaching and
learning. The symposium seeks contributions showing how to more effectively
teach AI, as well as how themes from AI may be used to enhance education
more broadly (for example, in introductory computing courses or as a means
for teaching computational thinking). We encourage the sharing of
innovative educational approaches that convey or leverage AI and its many
subfields, including robotics, machine learning, natural language
processing, computer vision, and others.

EAAI-17 is expected to include two invited talks (including a talk of the
recipient of the AAAI/EAAI Outstanding AI Educator Award 2016); a panel
with AI education experts; special tracks on Providing Research Experiences
for Undergraduate Students, Best Practices for Running an AI Research
Group, and AI for Education and Outreach; Model AI Assignments; the EAAI
NSG Challenge; and other exciting activities.


EAAI-17 provides a *Main Paper Track* with full-length papers (6 pages + 1
page of references) and extended abstract/poster contributions (2 pages,
including references) on all topics of relevance to EAAI-17. EAAI-17 also
provides a variety of *Special Tracks*, each with their own submission
requirements (see “Special Tracks” below).

EAAI-17 welcomes Main Track paper submissions on a variety of topics,
including (but not limited to) the following:

   - Educational resources, including pedagogical strategies, innovative
   assignments, and curricular development related to AI
   - Multi-disciplinary curriculum efforts highlighting the application of
   AI in other contexts (such as computational biology, algorithmic game
   theory, or computational economics) and/or foundational concepts of AI in
   other fields (such as philosophy, cognitive science, linguistics, or
   - The use of robotics and other tangible media in both AI courses and
   elsewhere in the curriculum
   - Software that assists the teaching/learning process, such as software
   to help visualize search spaces and search algorithms or software
   substrates that can be used by students to do projects
   - Resources and strategies for teaching specific AI sub-areas or topics
   (such as machine learning, robotics, computer vision, natural language
   processing, or game playing)
   - Strategies for situating AI within a wider computer-science curriculum
   - Ways to incorporate popular entertainment and media portrayal of AI
   into educational materials (such as in movies, news, or advertisements)
   - Real-world examples of AI deployments, described in sufficient detail
   to provide case studies and/or serve as useful springboards for other
   - Innovative means for integrating research as part of coursework in AI
   - Material for teaching ethical considerations with regard to AI

We also encourage submissions to the Educational Video Track within the
AAAI-17 Video Program.


*Special Paper Track: Providing Research Experiences for Undergraduate
Students (REU)*
Organizer:* Matthew E. Taylor*, Washington State University

The special track is about best practices about mentoring undergraduate
students and involving them in research, including (but not limited to) NSF
REU experiences. The submission requirements are the same as for the main

*Special Paper Track:* *Best Practices for Running an AI Research Group*

Organizer:* Eric Eaton*, University of Pennsylvania

Part of an educator’s job often involves running an effective research
group, both for the production of high quality research artifacts and the
education of junior researchers.  This special track will explore the best
practices for running an effective research group, including techniques for
managing numerous researchers and projects, running reading groups,
ensuring high quality research and experiments, and tools for publication
and software management.  Submissions to this track should focus on
practical topics and techniques of use to early career scientists.  The
submission requirements are the same as for the main track, with the
addition that it will also accept shorter papers (2-4 pages, including

*Special Paper Track: AI for Education and Outreach*

Organizer:* Sheila Tejada*, University of Southern California

The special track is about using AI in applications for education to
improve teaching and evaluation (for example, intelligent tutors or machine
learning for MOOCs) or improve learning and retention of students (for
example, educational robots, competitions, games, wearables, or K-12
outreach activities). The submission requirements are the same as for the
main track.

*Model AI Assignments (link to separate CFP below)*
Organizer:* Todd Neller*, Gettysburg College

Good project assignments for AI classes are hard to come by. If you believe
an assignment you have developed may be useful to other AI educators, we
encourage you to prepare it for broad dissemination and submit it to the
Model AI Assignments session.  If selected, the project will be made
available to other AI educators as a Model AI Assignment (
modelai.gettysburg.edu) and will be presented at EAAI (eaai.stanford.edu).
The submission requirements are described in the Call for Model AI
Assignments and at:
<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.aaai.org_Conferences_AAAI_2017_eaai17modelaicall.php&d=DQIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=1G8-h8YwCWqmXljBBBuDQtSIx3BOvfX8N7tmnJ4_1KY&s=vDuTZ1pWu7ecxKhBzHb66ILQw7uOt1NbLhH-6RaoO5M&e= >*

*EAAI-17 NSG Challenge: Widely-Accessible AI Robotics Tasks (link to
separate CFP below)*Organizer:* Zach Dodds*, Harvey Mudd College

It is difficult to share curricula that include both AI and Robotics.
Despite the difficulty, EAAI supports the development - and sharing - of
compelling AI Robotics curricula. The 2017 EAAI NSG*  challenge invites
compelling and accessible AI robotics tasks designed for educational use.
In a sense, this is a meta-robotics challenge, inviting AI robotics
challenges that maximize both curricular worth and easy deployment. The
submission requirements are described in the Call for Model AI Assignments
and at:


*(*Whereas DARPA has its "grand challenges," ours may seem not-so-grand –
but they're at least as challenging!)*


Full-length submissions to the main or special paper tracks of EAAI-17
should describe well-developed ideas and/or pedagogical examples.
Submissions are expected to provide in-depth arguments for the advantages
of the proposed ideas. For example, a proposed curriculum could be
evaluated by comparing it against existing ones or by presenting feedback
from students obtained via questionnaires. Formal evaluations are welcome
but not required. Extended abstract/poster submissions may highlight
preliminary or ongoing work.

Papers submitted to the Main Track must be formatted in AAAI two-column,
camera-ready style. Special Tracks may have their own submission
requirements, detailed above.  EAAI submissions should be anonymous
whenever possible, and should be formatted for double-blind review.
Full-length submissions may have up to 7 pages with Page 7 containing
nothing but references. Shorter submissions of 2-4 pages are permitted,
depending on the track; those page limits include references. The AAAI
copyright block is not required on submissions, but must be included on
final versions.


EAAI-17 will not consider any paper that, at the time of submission, is
under review for or has already been published or accepted for publication
in a journal or another conference. Once submitted to EAAI-17, authors may
not submit the paper elsewhere during EAAI/AAAI's review period. These
restrictions apply only to refereed journals and conferences, not to
unrefereed forums or workshops with a limited audience and without archival
proceedings. Authors must confirm that their submissions conform to these
requirements at the time of submission.

The EAAI-17 Co-Chairs

*Eric Eaton*
University of Pennsylvania

*Sven Koenig*
University of Southern California

Prof. Jim Boerkoel
Computer Science, Harvey Mudd College
homepage <https://urldefense.proofpoint.com/v2/url?u=http-3A__cs.hmc.edu_-7Eboerkoel_&d=DQIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=1G8-h8YwCWqmXljBBBuDQtSIx3BOvfX8N7tmnJ4_1KY&s=nQ8Kil2yVCcTKxsNmxpROpIv7N2rTsKNsv1qtVM58pY&e= > | Olin 1265 | x74522

Director: human experience & agent teamwork lab (HEATlab)
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