Navigating Uncertainty in Epidemic Contexts with Reinforcement Learning

AAAI 2024 pp. 23407-23408

doi:10.1609/AAAI.V38I21.30404 /aaai/2024/ondula2024aaai-navigating/

Abstract

My research integrates stochastic epidemic models with reinforcement learning to develop effective strategies or policies to inform operational decisions. The objective is to refine policies that are attuned to diverse outbreak dynamics and to offer a tool for informed planning in real-world settings.

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Cite

Text

Ondula. "Navigating Uncertainty in Epidemic Contexts with Reinforcement Learning." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I21.30404

Markdown

[Ondula. "Navigating Uncertainty in Epidemic Contexts with Reinforcement Learning." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/ondula2024aaai-navigating/) doi:10.1609/AAAI.V38I21.30404

BibTeX

@inproceedings{ondula2024aaai-navigating,
  title     = {{Navigating Uncertainty in Epidemic Contexts with Reinforcement Learning}},
  author    = {Ondula, Elizabeth Akinyi},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2024},
  pages     = {23407-23408},
  doi       = {10.1609/AAAI.V38I21.30404},
  url       = {https://mlanthology.org/aaai/2024/ondula2024aaai-navigating/}
}