AAAI-17 Special Track on Computational Sustainability
The Thirty-First Conference on Artificial Intelligence
February 4–9, 2016, San Francisco, California USA
Call for Papers
AAAI-17 Special Track on Computational Sustainability Paper Submission Site
2017 AAAI Author Kit
Timetable for Authors
- July 1, 2016 – September 9, 2016: Authors register on the AAAI web site
- September 9, 2016: Electronic abstracts due
- September 14, 2016: Electronic papers due
- October 27-29, 2016: Author feedback about initial reviews
- November 11, 2016: Notification of acceptance or rejection
- November 28, 2016: Camera-ready copy due
For additional information, please consult the main call for papers.
This special track invites research papers on novel concepts, models, algorithms, and systems, that address problems in computational sustainability. We are looking for a broad range of papers ranging from formal analysis to applied research. Examples include papers explaining how the research addresses specific computational problems, opportunities, or issues underlying sustainability challenges and papers describing a sustainability challenge or application that can be tackled using AI methods. Papers proposing general challenges and data sets for computational sustainability are also welcome. All AI topics that can address computational sustainability issues are appropriate, including machine learning, optimization, vision, and robotics, and others. Sustainability domains include natural resources, climate, and the environment (for example, climate change, atmosphere, water, oceans, forest, land, soil, biodiversity, species), economics and human behavior (for example, human well-being, poverty, infectious diseases, over-population, resource harvesting), energy (for example, renewable energy, smart grid, material discovery for fuel cell technology) and human-built systems (for example, transportation systems, cities, buildings, data centers, food systems, agriculture).
Special Track Cochairs
Bistra Dilkina (Georgia Institute of Technology, USA)
Sabine Storandt (Julius-Maximilians-Universität Würzburg, Germany)
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