AAAI 2023technical0 citations
Learning and Planning under Uncertainty for Conservation Decisions
Abstract
My research focuses on new techniques in machine learning and game theory to optimally allocate our scarce resources in multi-agent settings to maximize environmental sustainability. Drawing scientific questions from my close partnership with conservation organizations, I have advanced new lines of research in learning and planning under uncertainty, inspired by the low-data, noisy, and dynamic settings faced by rangers on the frontlines of protected areas.
BibTeX
@article{Xu_2024, title={Learning and Planning under Uncertainty for Conservation Decisions}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/26930}, DOI={10.1609/aaai.v37i13.26930}, abstractNote={My research focuses on new techniques in machine learning and game theory to optimally allocate our scarce resources in multi-agent settings to maximize environmental sustainability. Drawing scientific questions from my close partnership with conservation organizations, I have advanced new lines of research in learning and planning under uncertainty, inspired by the low-data, noisy, and dynamic settings faced by rangers on the frontlines of protected areas.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Xu, Lily}, year={2024}, month={Jul.}, pages={16139-16140} }