Canada CIFAR AI Chair
Pan-Canadian AI Strategy
Nathan Sturtevant is a Canada CIFAR AI Chair, a fellow at Amii, and a professor in the Department of Computing Science at the University of Alberta and the University of Denver. He is also the Director of Amii. He leads the Moving AI Lab, which has students both at the University of Alberta and the University of Denver.
Sturtevant’s research focuses on heuristic and combinatorial search problems, including both theoretical and applied approaches. Particular applications for his research include pathfinding and planning in memory-constrained real-time environments (e.g. commercial video games) as well as algorithms for building and using memory-based heuristics via large-scale search. His research has been implemented in commercial video games and he continues to collaborate with practitioners in the games industry.
- Prominent Paper Award, AIJ, 2021
- SoCS, Best Student Paper Award, 2018
- Symposium on Combinatorial Search, 2019 - 2018
- Senior Member, Association for the Advancement of Artificial Intelligence, 2017
- Outstanding Paper Award, Association for the Advancement of Artificial Intelligence, 2016
Stern, R., Sturtevant, N. R., Felner, A., Koenig, S., Ma, H., Walker, T. T., … & Boyarski, E. (2019). Multi-agent pathfinding: Definitions, variants, and benchmarks. In Twelfth Annual Symposium on Combinatorial Search.
Felner, A., Stern, R., Shimony, S. E., Boyarski, E., Goldenberg, M., Sharon, G., … & Surynek, P. (2017). Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges. In Tenth Annual Symposium on Combinatorial Search.
Sharon, G., Stern, R., Felner, A., & Sturtevant, N. R. (2015). Conflict-based search for optimal multi-agent pathfinding. Artificial Intelligence, 219, 40-66.
Goldenberg, M., Felner, A., Stern, R., Sharon, G., Sturtevant, N., Holte, R. C., & Schaeffer, J. (2014). Enhanced partial expansion A. Journal of Artificial Intelligence Research, 50, 141-187.
Sturtevant, N. R. (2012). Benchmarks for grid-based pathfinding. IEEE Transactions on Computational Intelligence and AI in Games, 4(2), 144-148.
CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.