Discovering Effective Policies for Land-Use Planning with Neuroevolution
Published in Environmental Data Science, 2025
Using a surrogate model to evaluate evolved prescriptive neural networks that allocate land use in order to minimize carbon emissions and land-change cost.
A shorter version appeared in the proceedings of the NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning and received the Best Pathway to Impact award. This work was originally presented at the AI for Good Summit 2023 and was presented as a poster at BayLearn 2024.
Recommended citation: D. Young et al., “Discovering effective policies for land-use planning with neuroevolution,” Environmental Data Science, vol. 4, p. e30, 2025. doi:10.1017/eds.2025.18
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