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Emergency decision making: A dynamic approach
Zhenyu Yu
Chuanfeng Han
Ma Ma
S.R. Hiltz, M.S.P., L. Plotnick, and P.C. Shih.
The dynamic nature of emergency decision making exerts difficulty to decision makers for achieving effective management. In this regard, we suggest a dynamic decision making model based on Markov decision process. Our model copes with the dynamic decision problems quantitatively and computationally, and has powerful expression ability to model the emergency decision problems. We use a wildfire scenario to demonstrate the implementation of the model, as well as the solution to the firefighting problem. The advantages of our model in emergency management domain are discussed and concluded in the last.
urn:ISBN:9780692211946
openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fidl.iscram.org%2F&genre=proceeding&title=Emergency%20decision%20making%3A%20A%20dynamic%20approach&stitle=ISCRAM%202014&issn=2411-3387&isbn=9780692211946&date=2014&spage=240&epage=244&aulast=Zhenyu%20Yu&au=Chuanfeng%20Han&au=Ma%20Ma&pub=The%20Pennsylvania%20State%20University&place=University%20Park%2C%20PA&sid=refbase%3AISCRAM
url:http://idl.iscram.org/show.php?record=1134
citekey:ZhenyuYu_etal2014
citation:Zhenyu Yu, Chuanfeng Han, & Ma Ma. (2014). Emergency decision making: A dynamic approach. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 240-244). University Park, PA: The Pennsylvania State University.
2014
ConferencePaper
text
Decision theory
Fires
Information systems
Markov processes
Risk management
Decision problems
Dynamic approaches
Dynamic decision making
Dynamic decision problem
Effective management
Emergency decision makings
Emergency management
Markov Decision Processes
Decision making
file:http://idl.iscram.org/files/yu/2014/1134_Yu_etal2014.pdf
The Pennsylvania State University
English
2411-3387
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management
2014
240
244
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