Mean-field games of optimal stopping : a relaxed solution approach
We consider the mean-field game where each agent determines the optimal time to exit the game by solving an optimal stopping problem with reward function depending on the density of the state processes of agents still present in the game. We place ourselves in the framework of relaxed optimal stoppi...
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sg-ntu-dr.10356-1442612020-10-26T01:05:31Z Mean-field games of optimal stopping : a relaxed solution approach Bouveret, Géraldine Dumitrescu, Roxana Tankov, Peter School of Physical and Mathematical Sciences Science Mean-field Games Optimal Stopping We consider the mean-field game where each agent determines the optimal time to exit the game by solving an optimal stopping problem with reward function depending on the density of the state processes of agents still present in the game. We place ourselves in the framework of relaxed optimal stopping, which amounts to looking for the optimal occupation measure of the stopper rather than the optimal stopping time. This framework allows us to prove the existence of a relaxed Nash equilibrium and the uniqueness of the associated value of the representative agent under mild assumptions. Further, we prove a rigorous relation between relaxed Nash equilibria and the notion of mixed solutions introduced in earlier works on the subject, and provide a criterion, under which the optimal strategies are pure strategies, that is, behave in a similar way to stopping times. Finally, we present a numerical method for computing the equilibrium in the case of potential games and show its convergence. 2020-10-26T01:05:31Z 2020-10-26T01:05:31Z 2020 Journal Article Bouveret, G., Dumitrescu, R., & Tankov, P. (2020). Mean-field games of optimal stopping : a relaxed solution approach. SIAM Journal on Control and Optimization, 58(4), 1795–1821. doi:10.1137/18M1233480 0363-0129 https://hdl.handle.net/10356/144261 10.1137/18M1233480 4 58 1795 1821 en SIAM Journal on Control and Optimization © 2020 Society for Industrial and Applied Mathematics (SIAM). All rights reserved. |
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Science Mean-field Games Optimal Stopping Bouveret, Géraldine Dumitrescu, Roxana Tankov, Peter Mean-field games of optimal stopping : a relaxed solution approach |
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We consider the mean-field game where each agent determines the optimal time to exit the game by solving an optimal stopping problem with reward function depending on the density of the state processes of agents still present in the game. We place ourselves in the framework of relaxed optimal stopping, which amounts to looking for the optimal occupation measure of the stopper rather than the optimal stopping time. This framework allows us to prove the existence of a relaxed Nash equilibrium and the uniqueness of the associated value of the representative agent under mild assumptions. Further, we
prove a rigorous relation between relaxed Nash equilibria and the notion of mixed solutions introduced in earlier works on the subject, and provide a criterion, under which the optimal strategies are pure strategies, that is, behave in a similar way to stopping times. Finally, we present a numerical method for computing the equilibrium in the case of potential games and show its convergence. |
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School of Physical and Mathematical Sciences |
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School of Physical and Mathematical Sciences Bouveret, Géraldine Dumitrescu, Roxana Tankov, Peter |
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Article |
author |
Bouveret, Géraldine Dumitrescu, Roxana Tankov, Peter |
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Bouveret, Géraldine |
title |
Mean-field games of optimal stopping : a relaxed solution approach |
title_short |
Mean-field games of optimal stopping : a relaxed solution approach |
title_full |
Mean-field games of optimal stopping : a relaxed solution approach |
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Mean-field games of optimal stopping : a relaxed solution approach |
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Mean-field games of optimal stopping : a relaxed solution approach |
title_sort |
mean-field games of optimal stopping : a relaxed solution approach |
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2020 |
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https://hdl.handle.net/10356/144261 |
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1683492957712285696 |