addressing current, important problems. To ensure
that this research has practical significance, many
research groups have partnered with regional government offices (such as the U.S. Fish and Wildlife
Service) to deploy the developed technology in
small-scale studies. In other cases, AI technology for
sustainability is beginning to reach consumers directly through commercial applications (for example, the
Green Driver project and smartphone app [Apple et
al. 2011]). Due to the interdisciplinary nature of sustainability problems, computational sustainability
research is also injecting computational thinking
into other fields and fostering the cross-fertilization
of ideas. Within the AI community, we hope that
continued research in this area will help broaden the
AAAI community, while providing a rich source of
important new problems to further advance the field
of artificial intelligence.
Apple, J.; Chang, P.; Clauson, A.; Dixon, H.; Fakhoury, H.;
Ginsberg, M.; Keenan, E.; Leighton, A.; Scavezze, K.; and
Smith, B. 2011. Green Driver: AI in a Microcosm. In Pro-
ceedings of the Twenty-Fifth AAAI Conference on Artifcial Intel-
ligence. Palo Alto, CA: AAAI Press.
Gomes, C. 2009. Computational Sustainability: Computational Methods for a Sustainable Environment, Economy,
and Society. The Bridge 39( 4): 5–13.
Griggs, D.; Stafford-Smith, M.; Gaffney, O.; Rockström, J.;
Öhman, M.; Shyamsundar, P.; Steffen, W.; Glaser, G.; Kanie,
N.; and Noble, I. 2013. Policy: Sustainable Development
Goals for People and Planet. Nature 495: 305–307.
United Nations Environment Programme. 1987. Our Common Future: Report of the World Commission on Environment and Development. Annex to General Assembly document A/42/427, Development and International
Cooperation: Environment. Report of the World Commission on Environment and Development. Nairobi, Kenya.
New York: United Nations.
United Nations General Assembly. 2005. Resolution adopted by the General Assembly on 16 September 2005: 2005
World Summit Outcome, Resolution A/60/1, adopted by the
General Assembly on 24 October 2005. New York: United
Eric Eaton is a lecturer in the Department of Computer and
Information Science and a member of the General Robotics,
Automation, Sensing, and Perception (GRASP) laboratory at
the University of Pennsylvania. Prior to joining Penn, he
was a visiting assistant professor in the computer science
department at Bryn Mawr College and a senior research scientist in the Artificial Intelligence Lab at Lockheed Martin
Advanced Technology Laboratories. His research focuses on
lifelong machine learning, knowledge transfer, and interactive AI.
Carla Gomes is a professor of computer science and the
director of the Institute for Computational Sustainability at
Cornell University. Her research themes include constraint
reasoning, mathematical programming, and machine learn-
ing for large-scale combinatorial problems. Recently, Gomes
has helped found the new field of computational
sustainability, which is her current main research
focus. Gomes is a fellow of AAAI and a fellow of the
American Association for the Advancement of Sci-
Brian Williams leads the Model-Based Embedded
and Robotic Systems group within the Computer
Science and Artificial Intelligence Laboratory
(CSAIL) at the Massachusetts Institute of Technology. His research concentrates on model-based
autonomy, model-based programming, and cooperative robotics. He is a fellow of AAAI, has served as
guest editor of the Artifcial Intelligence Journal and
has been on the editorial boards of the Journal of
Artifcial Intelligence Research and The MIT Press.
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