Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings
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Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
RL is used to predict the spatial progression of fire, which helps firefighters decide when to let a fire burn and when to stop it.
“In [266,267], RL is used to predict the spatial progression of fire.This helps firefighters decide when to let a fire burn and when to stop it [355].”
From Tackling climate change with machine learning (2023) · cites this paper as [266]
Cites
Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357 · see citing works
Mastering the game of Go with deep neural networks and tree search
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al. (2016) · Nature · doi:10.1038/nature16961 · Cited by 15,612 · see citing works
Mastering the game of Go without human knowledge
Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., et al. (2017) · Nature · doi:10.1038/nature24270 · Cited by 9,084 · see citing works
Bandit Based Monte-Carlo Planning
Kocsis, L., & Szepesvari, C. (2006) · European Conference on Machine Learning · doi:10.1007/11871842_29 · Cited by 4,073 · see citing works
Fire intensity, fire severity and burn severity: a brief review and suggested usage
Keeley, J. E. (2009) · International Journal of Wildland Fire · doi:10.1071/wf07049 · Cited by 2,287 · see citing works
A data mining approach to predict forest fires using meteorological data
Cortez, P. C., & Morais, A. D. J. R. (2007) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 347 · see citing works
Reinforcement learning for spatial processes
Forsell, N., Garçia, F., & Sabbadin, R. (2009) · HAL · Cited by 11 · see citing works
Flagged first, then by citations
Cited by
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Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
Li, W., & Hsu, C.-Y. (2022) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi11070385 · Cited by 147 · see citing works
- Authors
- Ganapathi Subramanian, S., & Crowley, M.
- Affiliations
- University of Waterloo (CA)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 285-291
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2795812275
- Cited by
- 11
- References
- 7
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 3 · 2022: 5 · 2019: 1
- FWCI
- 0.10
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence in Games
- Keywords
- forest fires, fire spread prediction, Monte Carlo tree search, A3C, deep reinforcement learning, ignition temperature
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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