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This paper considers a class of reinforcement-learning that belongs to the family of Learning Automata and provides a stochastic-stability analysis in strategic-form games. For this class of dynamics, convergence to pure Nash equilibria has…

Computer Science and Game Theory · Computer Science 2017-02-28 Georgios C. Chasparis

This paper studies robust time-inconsistent (TIC) linear-quadratic stochastic control problems, formulated by stochastic differential games. By a spike variation approach, we derive sufficient conditions for achieving the Nash equilibrium,…

Optimization and Control · Mathematics 2025-04-29 Bingyan Han , Chi Seng Pun , Hoi Ying Wong

We study a class of two-sided optimal control problems of general linear diffusions under a so-called Poisson constraint: the controlling is only allowed at the arrival times of an independent Poisson signal processes. We give a weak and…

Optimization and Control · Mathematics 2022-07-19 Harto Saarinen

We propose an implementable, neural network-based structure preserving probabilistic numerical approximation for a generalized obstacle problem describing the value of a zero-sum differential game of optimal stopping with asymmetric…

Numerical Analysis · Mathematics 2025-01-28 Ľubomír Baňas , Giorgio Ferrari , Tsiry Avisoa Randrianasolo

Constrained Markov games offer a formal mathematical framework for modeling multi-agent reinforcement learning problems where the behavior of the agents is subject to constraints. In this work, we focus on the recently introduced class of…

Machine Learning · Computer Science 2024-02-29 Philip Jordan , Anas Barakat , Niao He

In this paper we study Backward Stochastic Differential Equations with two reflecting right continuous with left limits obstacles (or barriers) when the noise is given by Brownian motion and a Poisson random measure mutually independent.…

Probability · Mathematics 2008-12-10 S. Hamadéne , H. Wang

We use martingale and stochastic analysis techniques to study a continuous-time optimal stopping problem, in which the decision maker uses a dynamic convex risk measure to evaluate future rewards. We also find a saddle point for an…

Probability · Mathematics 2009-11-23 Erhan Bayraktar , Ioannis Karatzas , Song Yao

We adapt the Stochastic Perron's method in Bayraktar and Sirbu (ArXiv: 1103.0538) to the case of double obstacle problems associated to Dynkin games. We construct, symmetrically, a viscosity sub-solution which dominates the upper value of…

Optimization and Control · Mathematics 2012-01-30 Erhan Bayraktar , Mihai Sirbu

We study a stochastic game where one player tries to find a strategy such that the state process reaches a target of controlled-loss-type, no matter which action is chosen by the other player. We provide, in a general setup, a relaxed…

Optimization and Control · Mathematics 2014-04-29 Bruno Bouchard , Ludovic Moreau , Marcel Nutz

We study a doubly reflected backward stochastic differential equation (BSDE) with integrable parameters and the related Dynkin game. When the lower obstacle $L$ and the upper obstacle $U$ of the equation are completely separated, we…

Probability · Mathematics 2015-07-07 Erhan Bayraktar , Song Yao

We study infinite horizon discounted-cost and ergodic-cost risk-sensitive zero-sum stochastic games for controlled continuous time Markov chains on a countable state space. For the discounted-cost game we prove the existence of value and…

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

This paper deals with N-person nonzero-sum discrete-time Markov games under a probability criterion, in which the transition probabilities and reward functions are allowed to vary with time. Differing from the existing works on the expected…

Probability · Mathematics 2025-05-16 Xin Guo , Xin Wen

The Hamilton-Jacobi-Bellman equation (HJB) associated with the time inhomogeneous singular control problem is a parabolic partial differential equation, and the existence of a classical solution is usually difficult to prove. In this paper,…

Optimization and Control · Mathematics 2014-10-14 Yipeng Yang

In this paper, we consider an expanding construction of a distributed control system, which is obtained by adding a new subsystem one after the other, until all $n$ subsystems, where $n \ge 2$, are included in the distributed control…

Optimization and Control · Mathematics 2014-09-30 Getachew K. Befekadu , Panos J. Antsaklis

In this paper, we investigate a new model of a linear-quadratic mean-field stochastic Stackelberg differential game with one leader and two followers, in which the leader is allowed to stop her strategy at a random time. Our overarching…

Optimization and Control · Mathematics 2021-06-08 Zhun Gou , Nan-jing Huang , Ming-hui Wang

We consider the following two-player game: using observational data, the leader chooses a prediction function for a response variable $Y$ from given covariates. The follower then reacts with an intervention on some covariates in the…

Machine Learning · Statistics 2026-05-19 Linus Kühne , Felix Schur , Jonas Peters

In this paper long-run risk sensitive optimisation problem is studied with dyadic impulse control applied to continuous-time Feller-Markov process. In contrast to the existing literature, focus is put on unbounded and non-uniformly ergodic…

Optimization and Control · Mathematics 2019-06-18 Marcin Pitera , Łukasz Stettner

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

In this paper we consider long-run risk sensitive average cost impulse control applied to a continuous-time Feller-Markov process. Using the probabilistic approach, we show how to get a solution to a suitable continuous-time Bellman…

Optimization and Control · Mathematics 2021-04-01 Damian Jelito , Marcin Pitera , Łukasz Stettner

The purpose of this paper is to provide a detailed probabilistic analysis of the optimal control of nonlinear stochastic dynamical systems of the McKean Vlasov type. Motivated by the recent interest in mean field games, we highlight the…

Probability · Mathematics 2013-03-26 René Carmona , Francois Delarue
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