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Connections between stochastic control and dynamic games

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Abstract

We consider duality relations between risk-sensitive stochastic control problems and dynamic games. They are derived from two basic duality results, the first involving free energy and relative entropy and resulting from a Legendre-type transformation, the second involving power functions. Our approach allows us to treat, in essentially the same way, continuous- and discrete-time problems, with complete and partial state observation, and leads to a very natural formal justification of the structure of the cost functional of the dual. It also allows us to obtain the solution of a stochastic game problem by solving a risk-sensitive control problem.

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References

  1. E. N. Barron and R. Jensen, Total risk aversion, stochastic optimal control, and differential games,Appl. Math. Optim. 19 (1989), 313–327.

    Article  MATH  MathSciNet  Google Scholar 

  2. A. Bensoussan and J. H. van Schuppen, Optimal control of partially observable stochastic systems with exponential-of-integral performance index,SIAM J. Control Optim. 23 (1985), 599–613.

    Article  MATH  MathSciNet  Google Scholar 

  3. D. P. Bertsekas,Dynamic Programming and Stochastic Control, Academic Press, London, 1976.

    Google Scholar 

  4. M. Boué and P. Dupuis, A Variational Representation for Certain Functionals of Brownian Motion, LCDS Report #95-7.

  5. C. D. Charalambous, The role of information state and adjoint in relating nonlinear output feedback risk-sensitive control and dynamic games, Preprint.

  6. C. D. Charalambous and R. J. Elliott, Classes of nonlinear partially observable stochastic optimal control problems with explicit optimal control laws, Preprint.

  7. J. D. Deuschel and D. W. Stroock,Large Deviations, Academic Press, New York, 1989.

    Google Scholar 

  8. P. Dupuis and R. S. Ellis, A Weak Convergence Approach to the Theory of Large Deviations, LCDS Report #93-6, Brown University, Providence, RI. Forthcoming book to be published by Wiley.

  9. E. Fernández-Gaucherand and S. I. Marcus, Risk-sensitive optimal control of hidden Markov models: a case study,Proc. 33rd CDC, 1994, pp. 1657–1662.

  10. W. H. Fleming and W. M. McEneany, Risk sensitive optimal control and differential games, inStochastic Theory and Adaptive Control (T. E. Duncan and B. Pasik-Duncan, eds.), Springer-Verlag, New York, 1992, 185–197.

    Google Scholar 

  11. W. H. Fleming and W. M. McEneany, Risk sensitive control on an infinite time horizon,SIAM J. Control Optim. 33 (1995), 1881–1915.

    Article  MATH  MathSciNet  Google Scholar 

  12. D. H. Jacobson, Optimal stochastic linear systems with exponential performance criteria and their relation to deterministic differential games,IEEE Trans. Automat. Control 18 (1973), 124–131.

    Article  MATH  Google Scholar 

  13. M. R. James, Asymptotic analysis of nonlinear stochastic risk-sensitive control and differential games,Math. Control Signals Systems 5 (1992), 401–417.

    Article  MATH  MathSciNet  Google Scholar 

  14. M. R. James, J. S. Baras, and R. J. Elliott, Risk sensitive control and dynamic games for partially observed discrete-time nonlinear systems,IEEE Trans. Automat. Control 39 (1994), 780–792.

    Article  MATH  MathSciNet  Google Scholar 

  15. R. S. Lipster and A. N. Shiryaev,Statistics of Random Processes, Vols. 1 and 2, Springer-Verlag, New York, 1988.

    Google Scholar 

  16. L. Meneghini, Modelli risolvibili per problemi di controllo di sistemi dinamici imprecisi multivariati, Thesis, University of Padova, 1994.

  17. T. Runolfsson, The equivalence between infinite-horizon optimal control of stochastic systems with exponential-of-integral performance index and stochastic differential games,IEEE Trans. Automat. Control 39 (1994), 1551–1563.

    Article  MATH  MathSciNet  Google Scholar 

  18. P. Whittle, Risk-sensitive-linear-quadratic-gaussian control,Adv. in Appl. Probab. 13 (1981), 764–777.

    Article  MATH  MathSciNet  Google Scholar 

  19. P. Whittle,Risk Sensitive Optimal Control, Wiley, New York, 1990.

    Google Scholar 

  20. P. Whittle, A risk sensitive maximum principle: The case of imperfect state observations,IEEE Trans. Automat. Control 36 (1991), 793–801.

    Article  MATH  MathSciNet  Google Scholar 

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Dai Pra, P., Meneghini, L. & Runggaldier, W.J. Connections between stochastic control and dynamic games. Math. Control Signal Systems 9, 303–326 (1996). https://doi.org/10.1007/BF01211853

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