Reports of the Workshops of the 31st AAAI Conference on Artificial Intelligence

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Authors: Monica Anderson, Roman Bartak, John S. Brownstein, David L. Buckeridge, Hoda Eldardiry and Christopher Geib
Date: Fall 2017
From: AI Magazine(Vol. 38, Issue 3)
Publisher: American Association for Artificial Intelligence
Document Type: Conference notes
Length: 8,397 words

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The AAAI-17 workshop program included 17 workshops covering a wide range of topics in AI. Workshops were held Sunday and Monday, February 45, 2017, at the Hilton San Francisco Union Square in San Francisco, California, USA.

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The AAAI-17 workshop program included 17 workshops that covered a wide range of topics in AI and were an excellent forum for exploring emerging approaches and task areas, for bridging the gaps between AI and other fields or between subfields of AI, for elucidating the results of exploratory research, or for critiquing existing approaches. Workshops were held Sunday and Monday, February 4-5, 2017, at the Hilton San Francisco Union Square in San Francisco, California, USA.

Workshop participants met and discussed issues with a selected focus--providing an informal setting for active exchange among researchers, developers, and users on topics of current interest. To foster interaction and exchange of ideas, the workshops were kept small, with 25-65 participants. Attendance was sometimes limited to active participants only, but most workshops also allowed general registration by other interested individuals. Most of the workshops were held on a single day.

Of the 17 workshops held, all but 2 (Increasing Diversity in AI and Developing Artificial Intelligence Startup Companies) were included in the AAAI digital library as technical reports.

Organizers of 5 of the AAAI workshops did not submit reports for publication in AI Magazine. This report contains summaries of 12 of the workshops that were submitted for publication by organizers. AI Magazine did not receive summaries for the remaining 5 summaries. The summaries included here were edited from the workshop websites or technical reports.

AI and OR for Social Good

The purpose of the AI and OR for Social Good workshop was to explore and promote the application of artificial intelligence (AI) and operations research (OR) for purposes of social good. There has been strong historical interest from both the AI and OR communities on this topic with a burst of AI activity in recent years in topics such as smart grids and optimized transport systems (both as part of a greater computational sustainability effort) while the OR community has long supported areas such as public-sector operations research (PSOR) whose stated objective is doing good with OR.

The workshop placed a special emphasis on bringing together members of the AI and OR communities (notably, the organizing committee consisted of members who overlap with both communities, namely Thomas Dietterich from Oregon State University, Steve Smith from Carnegie Mellon, Pascal Van Hentenryck from the University of Michigan, and Scott Sanner from the University of Toronto) who have been actively involved in addressing challenge problems for social good as well as the AI and OR technologies required to support their solution.

Applications areas targeted for the workshop included but were not limited to sustainable cities, smart government and social services, public service organizations, emergency preparedness, disaster response, public health, and humanitarian programs with problems ranging from data-driven predictive and prescriptive analytics through to logistical optimization. Technical topics targeted included all AI and...

Source Citation

Source Citation
Anderson, Monica, et al. "Reports of the Workshops of the 31st AAAI Conference on Artificial Intelligence." AI Magazine, vol. 38, no. 3, Fall 2017, p. 72+. Accessed 18 May 2021.
  

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