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In this paper we study a two person zero sum stochastic differential game in weak formulation. Unlike standard literature which uses strategy type of controls, the weak formulation allows us to consider the game with control against…

Probability · Mathematics 2012-10-01 Triet Pham , Jianfeng Zhang

We develop the linear programming approach to mean-field games in a general setting. This relaxed control approach allows to prove existence results under weak assumptions, and lends itself well to numerical implementation. We consider…

Optimization and Control · Mathematics 2020-11-24 Roxana Dumitrescu , Marcos Leutscher , Peter Tankov

We consider multi-player stopping games in continuous time. Unlike Dynkin games, in our games the payoff of each player is revealed after all the players stop. Moreover, each player can adjust her own stopping strategy by observing other…

Optimization and Control · Mathematics 2015-09-15 Zhou Zhou

We consider zero-sum stochastic differential games with possibly path-dependent controlled state. Unlike the previous literature, we allow for weak solutions of the state equation so that the players' controls are automatically of feedback…

Probability · Mathematics 2018-08-14 Dylan Possamaï , Nizar Touzi , Jianfeng Zhang

This paper considers mean field games in a multi-agent Markov decision process (MDP) framework. Each player has a continuum state and binary action. By active control, a player can bring its state to a resetting point. All players are…

Optimization and Control · Mathematics 2017-01-25 Minyi Huang , Yan Ma

We study a two-player zero-sum game in continuous time, where the payoff-a running cost-depends on a Brownian motion. This Brownian motion is observed in real time by one of the players. The other one observes only the actions of his…

Optimization and Control · Mathematics 2017-03-22 Fabien Gensbittel , Catherine Rainer

In this paper we consider an infinite horizon zero-sum differential game where the dynamics of each player and the running cost are also depending on the evolution of some discrete (switching) variables. In particular, such switching…

Optimization and Control · Mathematics 2020-03-05 Fabio Bagagiolo , Rosario Maggistro , Marta Zoppello

We study nonzero-sum stochastic games for continuous time Markov chains on a denumerable state space with risk sensitive discounted and ergodic cost criteria. For the discounted cost criterion we first show that the corresponding system of…

Optimization and Control · Mathematics 2016-03-09 Mrinal K. Ghosh , K. Suresh Kumar , Chandan Pal

The existence of stationary Markov perfect equilibria in stochastic games is shown under a general condition called "(decomposable) coarser transition kernels". This result covers various earlier existence results on correlated equilibria,…

Optimization and Control · Mathematics 2017-01-24 Wei He , Yeneng Sun

We propose and investigate a discrete-time mean field game model involving risk-averse agents. The model under study is a coupled system of dynamic programming equations with a Kolmogorov equation. The agents' risk aversion is modeled by…

Optimization and Control · Mathematics 2020-12-29 J. Frédéric Bonnans , Pierre Lavigne , Laurent Pfeiffer

We consider a nonzero-sum N-player Markov game on an abstract measurable state space with compact metric action spaces. The payoff functions are bounded Carath\'eodory functions and the transitions of the system are assumed to have a…

Optimization and Control · Mathematics 2023-05-09 François Dufour , Tomás Prieto-Rumeau

We develop an approach for two player constraint zero-sum and nonzero-sum stochastic differential games, which are modeled by Markov regime-switching jump-diffusion processes. We provide the relations between a usual stochastic optimal…

Optimization and Control · Mathematics 2023-01-31 Emel Savku

We consider a dynamic version of sender-receiver games, where the sequence of states follows an irreducible Markov chain observed by the sender. Under mild assumptions, we provide a simple characterization of the limit set of equilibrium…

Probability · Mathematics 2012-04-03 Jerome Renault , Eilon Solan , Nicolas Vieille

We consider a zero-sum stochastic differential game over elementary mixed feed-back strategies. These are strategies based only on the knowledge of the past state, randomized continuously in time from a sampling distribution which is kept…

Optimization and Control · Mathematics 2014-04-16 Mihai Sîrbu

The properties of value functions of time inhomogeneous optimal stopping problem and zero-sum game (Dynkin game) are studied through time dependent Dirichlet form. Under the absolute continuity condition on the transition function of the…

Optimization and Control · Mathematics 2013-06-28 Yipeng Yang

In this study, we investigate $N$-player stochastic differential games with regime switching, where the player dynamics are modulated by a finite-state Markov chain. We analyze the associated Nash system, which consists of a system of…

Probability · Mathematics 2025-02-26 Mingrui Wang , Prakash Chakraborty

We study the time-bounded reachability problem for continuous-time Markov decision processes (CTMDPs) and games (CTMGs). Existing techniques for this problem use discretisation techniques to break time into discrete intervals, and optimal…

Computer Science and Game Theory · Computer Science 2011-07-11 John Fearnley , Markus Rabe , Sven Schewe , Lijun Zhang

In this paper we study stochastic dynamic games with many players; these are a fundamental model for a wide range of economic applications. The standard solution concept for such games is Markov perfect equilibrium (MPE), but it is well…

Computer Science and Game Theory · Computer Science 2015-03-17 Sachin Adlakha , Ramesh Johari , Gabriel Y. Weintraub

This paper investigates the well-posedness of a type of state constraint ergodic Mean Field Game system in a bounded domain in which the Hamilton-Jacobi-Bellman equation is paired with an infinite Dirichlet boundary condition. In this…

Analysis of PDEs · Mathematics 2021-07-27 Mariya Sardarli

In this paper, we analyze mean-field game modulated by finite states markov chains. We first develop a sufficient stochastic maximum principle for the optimal control of a Markov-modulated stochastic differential equation (SDE) of…

Optimization and Control · Mathematics 2014-05-22 Yongming Tai