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Approximations of the optimal stopping problem in partial observation

Published online by Cambridge University Press:  14 July 2016

G. Mazziotto*
Affiliation:
CNET
*
Postal address: PAA/TIM/DRI, Centre National d'Etudes des Télécommunications, 38–40, Rue du Général Leclerc, 92131 Issy les Moulineaux, France.

Abstract

The resolution of the optimal stopping problem for a partially observed Markov state process reduces to the computation of a function — the Snell envelope — defined on a measure space which is in general infinite-dimensional. To avoid these computational difficulties, we propose in this paper to approximate the optimal stopping time as the limit of times associated to similar problems for a sequence of processes converging towards the true state. We show on two examples that these approximating states can be chosen such that the Snell envelopes can be explicitly computed.

Type
Research Paper
Copyright
Copyright © Applied Probability Trust 1986 

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References

[1] Beneš, V. E. (1982) Optimal stopping under partial observations, in Advances in Filtering and Optimal Stochastic Control, Lectures Notes on Control and Information Science 43, Springer-Verlag, Berlin, 1837.CrossRefGoogle Scholar
[2] Bensoussan, A. and Lions, J. L. (1978) Applications des inéquations variationnelles au contrôle stochastique. Dunod, Paris.Google Scholar
[3] Bismut, J. M. (1979) Un problème de contrôle stochastique avec observation partielle. Z. Wahrscheinlichkeitsth. 49, 6395.CrossRefGoogle Scholar
[4] Dellacherie, C. and Meyer, P. A. (1975), (1980) Probabilités et potentiel, Tomes 1, 2. Hermann, Paris.Google Scholar
[5] El Karoui, N. (1982) Les aspects probabilistes du contrôle stochastique. In récole d'été de Saint-Flour IX, 1979, Lecture Notes in Mathematics 876, Springer-Verlag, Berlin, 74239.Google Scholar
[6] Hakim-Dowek, M. (1982) Généralisation de l'enveloppe de Snell: Applications a un problème de contrôle de qualité. Thèse 3° Cycle, Université Pierre et Marie Curie, Paris.Google Scholar
[7] Ikeda, N. and Watanabe, S. (1981) Stochastic Differential Equations and Diffusion Processes. North-Holland, Amsterdam; Kodansha, Tokyo.Google Scholar
[8] Korezlioglu, H. and Mazziotto, G. (1984) Approximation of the non-linear filter by periodic sampling and quantization. In Analysis and Optimization of Systems, Lecture Notes in Control and Information Science 62, Springer-Verlag, Berlin, 553567.Google Scholar
[9] Kunita, H. (1971) Asymptotic behaviour of the non-linear filtering errors of Markov processes. J. Multivariate Anal. 1, 365393.CrossRefGoogle Scholar
[10] Lanery, E. (1983) Temps d'arrêt optimal des processus non bornés. Stochastics 11, 3363.CrossRefGoogle Scholar
[11] Menaldi, J. L. (1980) On the optimal stopping time problem for degenerate diffusions. SIAM J. Control Optim. 18, 697721.CrossRefGoogle Scholar
[12] Pardoux, E. and Talay, D. (1985) Discretization and simulation of stochastic differential equations. Acta Appl. Math. To appear.CrossRefGoogle Scholar
[13] Picard, J. (1962) Problèmes d'approximation en filtrage stochastique. Thèse 3° Cycle, Université Pierre et Marie Curie, Paris.Google Scholar
[14] Shiryayev, A. N. (1978) Optimal Stopping Rules. Springer-Verlag, Berlin.Google Scholar
[15] Stettner, L. (1983) On optimal stopping of Feller Markov processes with incomplete information in locally compact space. Preprint.Google Scholar
[16] Stettner, L. and Zabczyk, J. (1983) Optimal stopping for Feller processes. Preprint 284, Institute of Mathematics, Polish Academy of Sciences.Google Scholar
[17] Szpirglas, J. and Mazziotto, G. (1979) Modèle général de filtrage non linéaire et équations différentielles stochastiques associées. Ann. Inst. Henri Poincare 15, 147173.Google Scholar
[18] Zakai, M. (1969) On the optimal filtering of diffusion processes. Z. Wahrscheinlichkeitsth. 11, 230249.CrossRefGoogle Scholar