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Adaptive Dynamic Programming algorithm for finding online the equilibrium solution of the two-player zero-sum differential game

机译:在线寻找两人零和差分博弈均衡解的自适应动态规划算法

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This paper will present an Approximate/Adaptive Dynamic Programming (ADP) algorithm for determining online the Nash equilibrium solution for the two-player zero-sum differential game with linear dynamics and infinite horizon quadratic cost. The algorithm is built around an iterative method that has been developed in the control engineering community for solving the continuous-time game algebraic Riccati equation (CT-GARE) that is underlying the game problem. We here show how the ADP techniques will enhance the capabilities of the offline method allowing an online solution without the requirement of complete knowledge of the system dynamics.
机译:本文将提出一种近似/自适应动态规划(ADP)算法,用于在线确定具有线性动力学和无限地平线二次成本的两人零和差分游戏的纳什均衡解。该算法是围绕控制工程界开发的一种迭代方法构建的,该迭代方法用于解决游戏问题背后的连续时间游戏代数Riccati方程(CT-GARE)。我们在这里展示了ADP技术将如何增强离线方法的功能,从而允许在线解决方案,而无需完全了解系统动力学。

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