Model-free Q-learning designs for discrete-time zero-sum games with application to H-infinity control

  title={Model-free Q-learning designs for discrete-time zero-sum games with application to H-infinity control},
  author={Asma Al-Tamimi and Frank L. Lewis and Murad Abu-Khalaf},
  journal={2007 European Control Conference (ECC)},
In this paper, the optimal strategies for discrete-time linear system quadratic zero-sum games related to the H-infinity optimal control problem are solved in forward time without knowing the system dynamical matrices. The idea is to solve for an action dependent value function Q(x,u,w) of the zero-sum game instead of solving for the state dependent value function V(x) which satisfies a corresponding game algebraic Riccati equation (GARE). Since the state and actions spaces are continuous, two… CONTINUE READING
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Stabilizing a discrete , Constant , Linear System with Application to iterative Methods for Solving the Riccati Equation

  • B Krose S. Hagen
  • Linear quadratic Regulation using Reinforcement…
  • 1998

Neuronlike elements that can solve difficult learning control problems

  • R. S. Sutton A. G. Barto, C. W. Anderson
  • IEEE Trans . on Automat . Control
  • 1994

Approximate dynamic programming for real - time control and neural modeling

  • W. T. Miller
  • Neural Networks for Control

Special Issue on Neural Network feedback Control

  • F. L. Lewis
  • IEEE Trans . on Neural Networks

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