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Efficient sequential decision making under uncertainty (ESDEMUU)

Start date: May 1, 2011, End date: Apr 30, 2013,

"Many applications require efficient methods for automated decision making, such as control systems, crisis response, finance, logistics, network security, robotics and traffic management. These problems involve sequential learning and decision making under uncertainty in an unknown environment. As we have incomplete information about the state and dynamics of the environment, the outcome of any ...
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