CATALOGO DEI PRODOTTI DELLA RICERCA
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishWe study a family of optimal control problems under a set of controlled- loss constraints holding at different deterministic dates. The characterization of the associated value function by a Hamilton-Jacobi-Bellman equation usually calls for strong assumptions on the dynamics of the processes involved and the set of constraints. To treat this problem in absence of those assumptions, we first convert it into a state-constrained stochastic target problem and then solve the latter by a level-set approach. With this approach, state constraints are managed through an exact penalization technique.
| Titolo: | A Level-Set Approach for Stochastic Optimal Control Problems under Controlled-Loss Constraints |
| Autori: | |
| Data di pubblicazione: | 2020 |
| Rivista: | |
| Abstract: | We study a family of optimal control problems under a set of controlled- loss constraints holding at different deterministic dates. The characterization of the associated value function by a Hamilton-Jacobi-Bellman equation usually calls for strong assumptions on the dynamics of the processes involved and the set of constraints. To treat this problem in absence of those assumptions, we first convert it into a state-constrained stochastic target problem and then solve the latter by a level-set approach. With this approach, state constraints are managed through an exact penalization technique. |
| Handle: | http://hdl.handle.net/11562/1021101 |
| Appare nelle tipologie: | 01.01 Articolo in Rivista |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| OptCtrolReachApp.pdf | Documento in Post-print | Accesso ristretto | Utenti riconosciuti Richiedi una copia |
Copyright © 2021