16 citations · 103 across the 24 of their papers we have counts for
26 papers
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…
Markov -Potential Games
Xin Guo, Xinyu Li, Chinmay Maheshwari +2
We propose a new framework of Markov -potential games to study Markov games. We show that any Markov game with finite-state and finite-action is a Markov -potential game, and…
MFGLib: A Library for Mean-Field Games
Xin Guo, Anran Hu, Matteo Santamaria +2
Mean-field games (MFGs) are limiting models to approximate -player games, with a number of applications. Despite the ever-growing numerical literature on computation of MFGs, th…
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…
Theoretical Guarantees of Fictitious Discount Algorithms for Episodic Reinforcement Learning and Global Convergence of Policy Gradient Methods
Xin Guo, Anran Hu, Junzi Zhang
When designing algorithms for finite-time-horizon episodic reinforcement learning problems, a common approach is to introduce a fictitious discount factor and use stationary polici…
Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach
Haotian Gu, Xin Guo, Xiaoli Wei +1
One of the challenges for multi-agent reinforcement learning (MARL) is designing efficient learning algorithms for a large system in which each agent has only limited or partial in…
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…
Itô's formula for flows of measures on semimartingales
Xin Guo, Huyên Pham, Xiaoli Wei
We establish Itô's formula along flows of probability measures associated with general semimartingales; this generalizes existing results for flows of measures on Itô processes. Ou…
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…
A General Framework for 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…
Mean-Field Controls with Q-learning for Cooperative MARL: Convergence and Complexity Analysis
Haotian Gu, Xin Guo, Xiaoli Wei +1
Multi-agent reinforcement learning (MARL), despite its popularity and empirical success, suffers from the curse of dimensionality. This paper builds the mathematical framework to a…
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…
Transaction Cost Analytics for Corporate Bonds
Xin Guo, Charles-Albert Lehalle, Renyuan Xu
The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Tr…
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…
Consistency and Computation of Regularized MLEs for Multivariate Hawkes Processes
Xin Guo, Anran Hu, Renyuan Xu +1
This paper proves the consistency property for the regularized maximum likelihood estimators (MLEs) of multivariate Hawkes processes (MHPs). It also develops an alternating minimiz…
A class of stochastic games and moving free boundary problems
Xin Guo, Wenpin Tang, Renyuan Xu
In this paper we propose and analyze a class of -player stochastic games that include finite fuel stochastic games as a special case. We first derive sufficient conditions for t…
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…
Martingale Problem under Nonlinear Expectations
Xin Guo, Chen Pan, Shige Peng
We formulate and solve the martingale problem in a nonlinear expectation space. Unlike the classical work of Stroock and Varadhan (1969) where the linear operator in the associated…
A Note on - Optimal Stopping Problems
Xin Guo, Chen Pan, Shige Peng
We consider a class of discretionary stopping problems within the -framework. We first establish the well-definedness of the stopping problem under the -expectation, by showi…