16 citations · 103 across the 24 of their papers we have counts for
14 papers · 1 filter
Finite-player Optimal Stopping Games: Randomization, -potentiality, and Learning
Xin Guo, Mehdi Talbi, Qinxin Yan
Finite-player nonzero-sum optimal stopping games typically lead to coupled equilibrium systems whose complexity grows rapidly with the number of players. We introduce an independen…
Optimization frameworks and sensitivity analysis of Stackelberg mean-field games
Xin Guo, Anran Hu, Jiacheng Zhang
This paper proposes and studies a class of discrete-time finite-time-horizon Stackelberg mean-field games, with one leader and an infinite number of identical and indistinguishable…
MF-OMO: An Optimization Formulation of Mean-Field Games
Xin Guo, Anran Hu, Junzi Zhang
This paper proposes a new mathematical paradigm to analyze discrete-time mean-field games. It is shown that finding Nash equilibrium solutions for a general class of discrete-time…
Reinforcement learning for linear-convex models with jumps via stability analysis of feedback controls
Xin Guo, Anran Hu, Yufei Zhang
We study finite-time horizon continuous-time linear-convex reinforcement learning problems in an episodic setting. In this problem, the unknown linear jump-diffusion process is con…
Entropy Regularization for Mean Field Games with Learning
Xin Guo, Renyuan Xu, Thaleia Zariphopoulou
Entropy regularization has been extensively adopted to improve the efficiency, the stability, and the convergence of algorithms in reinforcement learning. This paper analyzes both…
Logarithmic regret for episodic continuous-time linear-quadratic reinforcement learning over a finite-time horizon
Matteo Basei, Xin Guo, Anran Hu +1
We study finite-time horizon continuous-time linear-quadratic reinforcement learning problems in an episodic setting, where both the state and control coefficients are unknown to t…
Interbank lending with benchmark rates: Pareto optima for a class of singular control games
Rama Cont, Xin Guo, Renyuan Xu
We analyze a class of stochastic differential games of singular control, motivated by the study of a dynamic model of interbank lending with benchmark rates. We describe Pareto opt…
Dynamic Programming Principles for Mean-Field Controls with Learning
Haotian Gu, Xin Guo, Xiaoli Wei +1
Dynamic programming principle (DPP) is fundamental for control and optimization, including Markov decision problems (MDPs), reinforcement learning (RL), and more recently mean-fiel…
MFGs for partially reversible investment
Haoyang Cao, Xin Guo
This paper analyzes a class of infinite-time-horizon stochastic games with singular controls motivated from the partially reversible problem. It provides an explicit solution for t…
Learning Mean-Field Games
Xin Guo, Anran Hu, Renyuan Xu +1
This paper presents a general mean-field game (GMFG) framework for simultaneous learning and decision-making in stochastic games with a large population. It first establishes the e…
Stochastic Games for Fuel Followers Problem: N vs MFG
Xin Guo, Renyuan Xu
In this paper we formulate and analyze an -player stochastic game of the classical fuel follower problem and its Mean Field Game (MFG) counterpart. For the -player game, we o…
Approximation of Mean Field Games to N-Player Stochastic Games, with Singular Controls
Haoyang Cao, Xin Guo, Joon Seok Lee
This paper establishes that -player stochastic games with singular controls, either of bounded velocity or of finite variation, can both be approximated by mean field games (MFG…
Impulse Control of Multi-dimensional Jump Diffusions in Finite Time Horizon
Yann-Shin Aaron Chen, Xin Guo
This paper analyzes a class of impulse control problems for multi-dimensional jump diffusions in the finite time horizon. Following the basic mathematical setup from Stroock and Va…
Impulse Control of Multidimensional Jump Diffusions
Mark H. A. Davis, Xin Guo, Guoliang Wu
This paper studies regularity property of the value function for an infinite-horizon discounted cost impulse control problem, where the underlying controlled process is a multidime…