Necessary stochastic maximum principle for dissipative systems on infinite time horizon

Orrieri, Carlo; Veverka, Petr

ESAIM: Control, Optimisation and Calculus of Variations, Tome 23 (2017) no. 1, pp. 337-371.

We develop a stochastic maximum principle for a finite-dimensional stochastic control problem in infinite horizon under a polynomial growth and joint monotonicity assumption on the coefficients. The second assumption generalizes the usual one in the sense that it is formulated as a joint condition for the drift and the diffusion term. The main difficulties concern the construction of the first and second order adjoint processes by solving backward equations on an unbounded time interval. The first adjoint process is characterized as a solution to a backward SDE, which is well-posed thanks to a duality argument. The second one can be defined via another duality relation written in terms of the Hamiltonian of the system and linearized state equation. Some known models verifying the joint monotonicity assumption are discussed as well.

Classification : 93E20, 60H10, 49K45
Mots clés : Stochastic maximum principle, dissipative systems, backward stochastic differential equation, stochastic discounted control problem, infinite time horizon, necessary conditions for optimality

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