English

Discovering Transition Pathways Towards Coviability with Machine Learning

Computers and Society 2023-01-25 v1 Artificial Intelligence

Abstract

Coviability refers to the multiple socio-ecological arrangements and governance structures under which humans and nature can coexist in functional, fair, and persistent ways. Transitioning to a coviable state in environmentally degraded and socially vulnerable territories is challenging. This paper presents an ongoing French-Brazilian joint research project combining machine learning, agroecology, and social sciences to discover coviability pathways that can be adopted and implemented by local populations in the North-East region of Brazil.

Cite

@article{arxiv.2301.10023,
  title  = {Discovering Transition Pathways Towards Coviability with Machine Learning},
  author = {Laure Berti-Equille and Rafael L. G. Raimundo},
  journal= {arXiv preprint arXiv:2301.10023},
  year   = {2023}
}

Comments

5 pages, 1 figure

R2 v1 2026-06-28T08:18:40.376Z