Maximizing the Spread of Cascades Using Network Design
Abstract
We introduce a new optimization framework to maximize the expected spread of cascades in networks. Our model allows a rich set of actions that directly manipulate cascade dynamics by adding nodes or edges to the network. Our motivating application is one in spatial conservation planning, where cade models the dispersal of wild animals through a fragmented landscape. We propose a mixed integer programming (MIP) formulation that combines elements from network design and stochastic optimization. Our approach results in solutions with stochastic optimality guarantees and points to conservation strategies that are fundamentally different from naive approaches.
Cite
Text
Sheldon et al. "Maximizing the Spread of Cascades Using Network Design." Conference on Uncertainty in Artificial Intelligence, 2010.Markdown
[Sheldon et al. "Maximizing the Spread of Cascades Using Network Design." Conference on Uncertainty in Artificial Intelligence, 2010.](https://mlanthology.org/uai/2010/sheldon2010uai-maximizing/)BibTeX
@inproceedings{sheldon2010uai-maximizing,
title = {{Maximizing the Spread of Cascades Using Network Design}},
author = {Sheldon, Daniel and Dilkina, Bistra and Elmachtoub, Adam N. and Finseth, Ryan and Sabharwal, Ashish and Conrad, Jon and Gomes, Carla P. and Shmoys, David B. and Allen, William and Amundsen, Ole and Vaughan, William},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2010},
pages = {517-526},
url = {https://mlanthology.org/uai/2010/sheldon2010uai-maximizing/}
}