We present a version of the stochastic maximum principle (SMP) for ergodic control problems. In particular we give necessary (and sufficient) conditions for optimality for controlled dissipative systems in finite dimensions. The strategy we employ is mainly built on duality techniques. We are able to construct a dual process for all positive times via the analysis of a suitable class of perturbed linearized forward equations. We show that such a process is the unique bounded solution to a backward SDE on infinite horizon from which we can write a version of the SMP.
Orrieri, C., Tessitore, G., Veverka, P. (2019). Ergodic Maximum Principle for Stochastic Systems. APPLIED MATHEMATICS AND OPTIMIZATION, 79(3), 567-591 [10.1007/s00245-017-9448-7].
Ergodic Maximum Principle for Stochastic Systems
Tessitore, G
;
2019
Abstract
We present a version of the stochastic maximum principle (SMP) for ergodic control problems. In particular we give necessary (and sufficient) conditions for optimality for controlled dissipative systems in finite dimensions. The strategy we employ is mainly built on duality techniques. We are able to construct a dual process for all positive times via the analysis of a suitable class of perturbed linearized forward equations. We show that such a process is the unique bounded solution to a backward SDE on infinite horizon from which we can write a version of the SMP.
| File | Dimensione | Formato | |
|---|---|---|---|
|
ErgodicMaximumPrincipleForStoc.pdf
Solo gestori archivio
Tipologia di allegato:
Publisher’s Version (Version of Record, VoR)
Dimensione
495.63 kB
Formato
Adobe PDF
|
495.63 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
