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This paper presents an online adaptive optimal control algorithm based on policy iteration reinforcement learning techniques to solve the continuous-time Stackelberg games with infinite horizon for linear systems. This adaptive optimal control method finds in real-time approximations of the optimal value and the Stackelberg-equilibrium solution, while also guaranteeing closed-loop stability. The optimal-adaptive...
An approximate online solution is developed for a two-player zero-sum game subject to continuous-time nonlinear uncertain dynamics and an infinite horizon quadratic cost. A novel actor-critic-identifier (ACI) structure is used to implement the Policy Iteration (PI) algorithm, wherein a robust dynamic neural network (DNN) is used to asymptotically identify the uncertain system, and a critic NN is used...
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