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- W2168251564 abstract "The paper is concerned with nonlinear stochastic minimax dynamic games which are subject to noisy measurements. The minimizing players are control inputs while the maximizing players are square-integrable stochastic processes. First, the minimax dynamic game is formulated using an information state, which satisfies a stochastic partial differential equation. Subsequently, a separation theorem is derived between the estimation and the control problems. Second, a certainty-equivalence principle is introduced along the lines of Whittle (1991), by defining the future stress, the past stress, the minimum stress and the certainty-equivalence controller. Third, the separation theorem and the certainty-equivalence principle are applied to solve the linear-quadratic-Gaussian minimax game. The optimal control and the certainty-equivalence control are shown to be identical. The results of the paper generalize the L/sup 2/-gain of deterministic systems to stochastic analogs; they are related to the controller design of stochastic risk-sensitive control and minimax deterministic dynamic games." @default.
- W2168251564 created "2016-06-24" @default.
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- W2168251564 date "2003-01-22" @default.
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- W2168251564 title "Stochastic nonlinear minimax dynamic games with noisy measurements" @default.
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- W2168251564 doi "https://doi.org/10.1109/cdc.1999.833349" @default.
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