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• W2112103082 abstract "In this correspondence, adaptive critic approximate dynamic programming designs are derived to solve the discrete-time zero-sum game in which the state and action spaces are continuous. This results in a forward-in-time reinforcement learning algorithm that converges to the Nash equilibrium of the corresponding zero-sum game. The results in this correspondence can be thought of as a way to solve the Riccati equation of the well-known discrete-time H <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>infin</sub> optimal control problem forward in time. Two schemes are presented, namely: 1) a heuristic dynamic programming and 2) a dual-heuristic dynamic programming, to solve for the value function and the costate of the game, respectively. An H <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>infin</sub> autopilot design for an F-16 aircraft is presented to illustrate the results" @default.
• W2112103082 created "2016-06-24" @default.
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• W2112103082 date "2007-02-01" @default.
• W2112103082 modified "2023-10-05" @default.
• W2112103082 title "Adaptive Critic Designs for Discrete-Time Zero-Sum Games With Application to $H_{infty}$ Control" @default.
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• W2112103082 doi "https://doi.org/10.1109/tsmcb.2006.880135" @default.
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• W2112103082 hasPublicationYear "2007" @default.
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