AI and Decision Support for Sustainable Socio-Ecosystems
Abstract
The conservation and the restoration of biodiversity, in accordance with human well-being, is a necessary condition for the realization of several Sustainable Development Goals. However, there is still an important gap between biodiversity research and the management of natural areas. This research project aims to reduce this gap by proposing spatial planning methods that robustly and accurately integrate socio-ecological issues. Artificial intelligence, and notably Constraint Programming, will play a central role and will make it possible to remove the methodological obstacles that prevent us from properly addressing the complexity and heterogeneity of sustainability issues in the management of ecosystems. The whole will be articulated in three axes: (i) integrate socio-ecological dynamics into spatial planning, (ii) rely on adequate landscape metrics in spatial planning, (iii) scaling up spatial planning methods performances. The main study context of this project is the sustainable management of tropical forests, with a particular focus on New Caledonia and West Africa.
BibTeX
@inproceedings{ijcai2023p707,
title = {AI and Decision Support for Sustainable Socio-Ecosystems},
author = {Justeau-Allaire, Dimitri},
booktitle = {Proceedings of the Thirty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-23}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Edith Elkind},
pages = {6370--6377},
year = {2023},
month = {8},
note = {AI for Good - Projects},
doi = {10.24963/ijcai.2023/707},
url = {https://doi.org/10.24963/ijcai.2023/707},
}