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Stochastics
An International Journal of Probability and Stochastic Processes
Volume 89, 2017 - Issue 1: Festschrift for Bernt Øksendal
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Original Articles

On the policy improvement algorithm in continuous time

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Pages 348-359 | Received 28 Sep 2015, Accepted 04 May 2016, Published online: 23 May 2016

References

  • B.T. Doshi, Continuous time control of markov processes on an arbitrary state space: Discounted rewards, Ann. Stat. 4(6) (1976), pp. 1219–1235.
  • W.H. Fleming, and H.M. Soner, Controlled Markov Processes and Viscosity Solutions, 2nd ed., Springer-Verlag, New York, 2006.
  • A. Friedman, Partial Differential Equations of Parabolic Type, Prentice-Hall, Englewood Cliffs, NJ, 1964.
  • A. Hordijk, and M.L. Puterman, On the convergence of policy iteration in finite state undiscounted Markov decision processes: The unichain case, Math. Oper. Res. 12(1) (1987), pp. 163–176.
  • R.A. Howard, Dynamic Programming and Markov Processes, MIT Press, Cambridge, 1960.
  • S.D. Jacka, A. Mijatović and D. Širaj, Policy Improvement Algorithm for Controlled Multidimensional Diffusion Processes, in preparation.
  • S.D. Jacka, A. Mijatović and D. Širaj, Coupling of Diffusions and the Policy Improvement Algorithm for a Finite Horizon Problem, in preparation.
  • S.P. Meyn, The policy iteration algorithm for average reward Markov decision processes with general state space, IEEE Trans. Autom. Control 42(12) (1997), pp. 1663–1680.
  • M.S. Santos, and J. Rust, Convergence properties of policy iteration, SIAM J. Control Optim. 42(6) (2004), pp. 2094–2115.

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