Compactification in optimal control of McKean‐Vlasov stochastic differential equations
Autor: | Mohamed Amine Mezerdi |
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Přispěvatelé: | Institut de Mathématiques de Toulon - EA 2134 (IMATH), Université de Toulon (UTLN), Université Mohamed Khider de Biskra (BISKRA) |
Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Control and Optimization
Applied Mathematics 010102 general mathematics Optimal control 01 natural sciences 010104 statistics & probability Stochastic differential equation Control and Systems Engineering Applied mathematics Compactification (mathematics) 0101 mathematics [MATH]Mathematics [math] Software Mathematics |
Zdroj: | Optimal Control Applications and Methods Optimal Control Applications and Methods, Wiley, 2021, 42 (4), pp.1161-1177. ⟨10.1002/oca.2721⟩ |
ISSN: | 0143-2087 1099-1514 |
DOI: | 10.1002/oca.2721⟩ |
Popis: | International audience; We study existence and approximation of optimal controls for systems governed by McKean-Vlasov stochastic differential equations. It is well known in simple examples that in the absence of convexity conditions, the strict control problem has no optimal solution. The compactification of the set of such strict admissible controls leads to measure valued controls called relaxed controls. The space of relaxed controls enjoys nice topological properties. We prove that under pathwise uniqueness of solutions of the state equation, the relaxed state process is continuous with respect to the control variable. This means that the relaxed and strict control problems have the same value function. Moreover, we show, under merely continuity of the coefficients, that an optimal control exists in the space of relaxed controls. Under additional convexity hypothesis, we show that the optimal relaxed control is a strict control. These two results extend known results to general nonlinear MVSDEs, under minimal assumptions on the coefficients. |
Databáze: | OpenAIRE |
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