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

@article{AlTamimi2007ModelfreeQD,
  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)},
  year={2007},
  pages={1668-1675}
}
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
Highly Cited
This paper has 148 citations. REVIEW CITATIONS
57 Citations
9 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 57 extracted citations

148 Citations

0102030'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 148 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-9 of 9 references

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

Similar Papers

Loading similar papers…