Article1995

General necessary conditions for partially observed optimal stochastic controls

58 citations0/0 files storedJournal of Applied Probability

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Stochastic processes and financial applications Stability and Controllability of Differential Equations Adaptive Dynamic Programming Control

Abstract

The partially observed control problem is considered for stochastic processes with control entering into the diffusion and the observation. The maximum principle is proved for the partially observable optimal control. A pure probabilistic approach is used, and the adjoint processes are characterized as solutions of related backward stochastic differential equations in finite-dimensional spaces. Most of the derivation is identified with that of the completely observable case.

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References

1990A General Stochastic Maximum Principle for Optimal Control Problems 1994Necessary Conditions for Optimal Control of Stochastic Systems with Random Jumps 1983Maximum principle and dynamic programming approaches of the optimal control of partially observed diffusions 1993On the Necessary Conditions of Optimal Controls for Stochastic Partial Differential Equations 1968Optimal Control of Partially Observable Diffusions 1989The Partially Observed Stochastic Minimum Principle

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1999Open Problems on Backward Stochastic Differential Equations 2010Maximum Principle for Partially-Observed Optimal Control of Fully-Coupled Forward-Backward Stochastic Systems 2009General Maximum Principles for Partially Observed Risk-Sensitive Optimal Control Problems and Applications to Finance 2010Maximum Principles for a Class of Partial Information Risk-Sensitive Optimal Controls 2020An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems 2016Linear‐Quadratic Optimal Control Problem for Partially Observed Forward‐Backward Stochastic Differential Equations of Mean‐Field Type

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