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We study a McKean-Vlasov Forward-Backward Stochastic Differential Equation (FBSDE) in connection with the theory of Stochastic Differential Mean-Field games, particularly the weak (non-fully coupled) formulation described in Section 3.3.1…

Optimization and Control · Mathematics 2026-05-08 Hector Sanchez Morgado , Jesus Sierra

Mechanism design is a well-established game-theoretic paradigm for designing games to achieve desired outcomes. This paper addresses a closely related but distinct concept, equilibrium design. Unlike mechanism design, the designer's…

Computer Science and Game Theory · Computer Science 2024-08-20 Muhammad Najib , Giuseppe Perelli

Stochastic differential games are considered in a non-Markovian setting. Typically, in stochastic differential games the modulating process of the diffusion equation describing the state flow is taken to be Markovian. Then Nash equilibria…

Information Theory · Computer Science 2007-07-13 Erhan Bayraktar , H. Vincent Poor

In many multi-player interactions, players incur strictly positive costs each time they execute actions e.g. 'menu costs' or transaction costs in financial systems. Since acting at each available opportunity would accumulate prohibitively…

Multiagent Systems · Computer Science 2024-08-02 David Mguni

This paper considers stochastic-constrained stochastic optimization where the stochastic constraint is to satisfy that the expectation of a random function is below a certain threshold. In particular, we study the setting where data samples…

Optimization and Control · Mathematics 2026-01-27 Yeongjong Kim , Dabeen Lee

This article is concerned with stochastic control problems for backward doubly stochastic differential equations of mean-field type, where the coefficient functions depend on the joint distribution of the state process and the control…

Probability · Mathematics 2022-05-26 Jian Song , Meng Wang

We develop a probabilistic approach to continuous-time finite state mean field games. Based on an alternative description of continuous-time Markov chain by means of semimartingale and the weak formulation of stochastic optimal control, our…

Probability · Mathematics 2018-08-24 Rene Carmona , Peiqi Wang

In this paper we estimate the tracking error of a fixed gain stochastic approximation scheme. The underlying process is not assumed Markovian, a mixing condition is required instead. Furthermore, the updating function may be discontinuous…

Probability · Mathematics 2018-10-17 Huy N. Chau , Chaman Kumar , Miklós Rásonyi , Sotirios Sabanis

In this paper, a partially observed stochastic linear Stackelberg differential game with mean-variance criteria is studied. Randomness comes from Brownian motions and Poisson random measures. which leads to a circular dependency. We follow…

Optimization and Control · Mathematics 2026-01-27 Jingtao Lin , Jingtao Shi

We provide a general approach to reformulating any continuous-time stochastic Stackelberg differential game under closed-loop strategies as a single-level optimisation problem with target constraints. More precisely, we consider a…

Optimization and Control · Mathematics 2026-05-14 Camilo Hernández , Nicolás Hernández Santibáñez , Emma Hubert , Dylan Possamaï

We introduce an efficient numerical scheme for continuous time Dynkin games under model uncertainty. We use the Skorokhod embedding in order to construct recombining tree approximations. This technique allows us to determine convergence…

Probability · Mathematics 2018-02-20 Benjamin Gottesman , Yan Dolinsky

We analyze an optimal stopping problem with a constraint on the expected cost. When the reward function and cost function are Lipschitz continuous in state variable, we show that the value of such an optimal stopping problem is a continuous…

Optimization and Control · Mathematics 2017-08-08 Erhan Bayraktar , Song Yao

We study singular stochastic control of a two dimensional stochastic differential equation, where the first component is linear with random and unbounded coefficients. We derive existence of an optimal relaxed control and necessary…

Optimization and Control · Mathematics 2008-12-08 Daniel Andersson

This paper studies a class of mean-field control (MFC) problems with singular controls under general dynamic state-control-law constraints. We first propose a customized relaxed control formulation to cope with the dynamic mixed constraints…

Optimization and Control · Mathematics 2026-04-28 Lijun Bo , Jingfei Wang , Xiang Yu

In this note, we study a class of indefinite stochastic McKean-Vlasov linear-quadratic (LQ in short) control problem under the control taking nonnegative values. In contrast to the conventional issue, both the classical dynamic programming…

Optimization and Control · Mathematics 2023-10-05 Xun Li , Liangquan Zhang

In this paper, we study a stochastic optimal control problem under degenerate G-expectation. By using implied partition method, we show that the approximation result for admissible controls still hold. Based on this result, we prove that…

Optimization and Control · Mathematics 2022-10-19 Xiaojuan Li

In the paper, we use the equivalent formulation of a finite state mean field game as a control problem with mixed constraints to study the dependence of solutions to finite state mean field game on an initial distribution of players. We…

Optimization and Control · Mathematics 2021-09-16 Yurii Averboukh

In this paper we study the stochastic control problem of partially observed (multi-dimensional) stochastic system driven by both Brownian motions and fractional Brownian motions. In the absence of the powerful tool of Girsanov…

Optimization and Control · Mathematics 2023-08-22 Yueyang Zheng , Yaozhong Hu

In this paper, we first give the existence and uniqueness theorems for generalized mean-filed delay stochastic differential equations (GMFDSDEs) and mean-field anticipated backward stochastic differential equations (MFABSDEs). Then we study…

Optimization and Control · Mathematics 2017-08-14 Hancheng Guo , Jie Xiong , Jiayu Zheng

In this paper, we study the $extended$ mean field control problem, which is a class of McKean-Vlasov stochastic control problem where the state dynamics and the reward functions depend upon the joint (conditional) distribution of the…

Probability · Mathematics 2022-04-06 Mao Fabrice Djete
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