Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2512.00934 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866915645675798528 |
|---|---|
| author | Guatteri, Giuseppina Masiero, Federica Wessels, Lukas |
| author_facet | Guatteri, Giuseppina Masiero, Federica Wessels, Lukas |
| contents | We extend Peng's maximum principle to the case of stochastic delay differential equations of mean-field type. More precisely, the coefficients of our control problem depend on the state, on the past trajectory and on its expected value. Moreover, the control enters the noise coefficient and the control domain may be non-convex. Our approach is based on a lifting of the state equation to an infinite dimensional Hilbert space that removes the explicit delay in the state equation. The main ingredient in the proof of the maximum principle is a precise asymptotic for the expectation of the first order variational process, which allows us to neglect the corresponding second order terms in the expansion of the cost functional. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_00934 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Peng's Maximum Principle for Stochastic Delay Differential Equations of Mean-Field Type Guatteri, Giuseppina Masiero, Federica Wessels, Lukas Probability Optimization and Control We extend Peng's maximum principle to the case of stochastic delay differential equations of mean-field type. More precisely, the coefficients of our control problem depend on the state, on the past trajectory and on its expected value. Moreover, the control enters the noise coefficient and the control domain may be non-convex. Our approach is based on a lifting of the state equation to an infinite dimensional Hilbert space that removes the explicit delay in the state equation. The main ingredient in the proof of the maximum principle is a precise asymptotic for the expectation of the first order variational process, which allows us to neglect the corresponding second order terms in the expansion of the cost functional. |
| title | Peng's Maximum Principle for Stochastic Delay Differential Equations of Mean-Field Type |
| topic | Probability Optimization and Control |
| url | https://arxiv.org/abs/2512.00934 |