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Reflected diffusions naturally arise in many problems from applications ranging from economics and mathematical biology to queueing theory. In this paper we consider a class of infinite time-horizon singular stochastic control problems for…

Optimization and Control · Mathematics 2017-11-13 Giorgio Ferrari

We consider a finite-horizon, zero-sum game in which both players control a stochastic differential equation by invoking impulses. We derive a control randomization formulation of the game and use the existence of a value for the randomized…

Optimization and Control · Mathematics 2025-05-13 Magnus Perninge

We consider a reach-avoid differential game, in which one of the players aims to steer the system into a target set without violating a set of state constraints, while the other player tries to prevent the first from succeeding; the system…

Optimization and Control · Mathematics 2014-10-30 Jaime F. Fisac , Mo Chen , Claire J. Tomlin , S. Shankar Sastry

We consider a Markovian stochastic control problem with model uncertainty. The controller (intelligent player) observes only the state, and, therefore, uses feed-back (closed-loop) strategies. The adverse player (nature) who does not have a…

Optimization and Control · Mathematics 2014-04-09 Mihai Sîrbu

In a multitime hybrid differential game with mechanical work payoff, the multitime upper value function and the multitime lower value function are viscosity solutions of original PDEs of type Hamilton-Jacobi-Isaacs.

Analysis of PDEs · Mathematics 2017-03-20 Constantin Udrişte , Elena-Laura Otobîcu , Ionel Ţevy

In this paper, we prove a comparison result between semicontinuous viscosity sub and supersolutions growing at most quadratically of second-order degenerate parabolic Hamilton-Jacobi-Bellman and Isaacs equations. As an application, we…

Analysis of PDEs · Mathematics 2010-02-12 Francesca Da Lio , Olivier Ley

In the framework of stochastic zero-sum differential games, we establish a verification theorem, inspired by those existing in stochastic control, to provide sufficient conditions for a pair of feedback controls to form a Nash equilibrium.…

Optimization and Control · Mathematics 2025-10-15 Carlo Ciccarella , Francesco Russo

In this paper, we provide an estimate for the solutions of reflected backward stochastic differential equations (RBSDEs) driven by a Markov chain, derive a continuous dependence property for their solutions with respect to the parameters of…

Probability · Mathematics 2015-05-14 Zhe Yang , Dimbinirina Ramarimbahoaka , Robert J. Elliott

We study a finite-horizon differential game of pursuit-evasion like, between a single player and a mass of agents. The player and the mass directly control their own evolution, which for the mass is given by a first order PDE of transport…

Optimization and Control · Mathematics 2025-02-28 Fabio Bagagiolo , Rossana Capuani , Luciano Marzufero

In this paper, we introduce a new method to study the doubly reflected backward stochastic differential equation driven by G-Brownian motion (G-BSDE). Our approach involves approximating the solution through a family of penalized reflected…

Probability · Mathematics 2024-03-28 Hanwu Li , Ning Ning

In this paper we advocate for Isaacs' method for the solution of differential games to be applied to the solution of optimal control problems. To make the argument, the vehicle employed is Pontryagin's canonical optimal control example,…

Optimization and Control · Mathematics 2023-03-31 Meir Pachter , Isaac E Weintraub

In this paper, we prove the existence and uniqueness of the solution to reflected backward doubly stochastic differential equations driven by Teugels martingales associated with a L\'evy process where the barrier process is not necessarily…

Probability · Mathematics 2021-07-13 Mohamed Marzougue

This paper is concerned with a new type of differential game problems of forwardbackward stochastic systems. There are three distinguishing features: Firstly, our game systems are forward-backward doubly stochastic differential equations,…

Optimization and Control · Mathematics 2015-10-09 Eddie C. M. Hui , Hua Xiao

In this paper, we examine a class of $\alpha$-potential stochastic differential games with random coefficients via the backward stochastic differential equations (BSDEs) approach. Specifically, we show that the first and second order linear…

Optimization and Control · Mathematics 2025-07-18 Xin Guo , Xun Li , Liangquan Zhang

In the first part of the paper, we study reflected backward stochastic differential equations (RBSDEs) with lower obstacle which is assumed to be right upper-semicontinuous but not necessarily right-continuous. We prove existence and…

Probability · Mathematics 2017-05-11 Miryana Grigorova , Peter Imkeller , Elias Offen , Youssef Ouknine , Marie-Claire Quenez

This paper studies a two-player nonzero-sum stochastic differential game governed by a controlled convection-diffusion stochastic partial differential equation (SPDE) with spatially heterogeneous coefficients. The diffusion and transport…

Probability · Mathematics 2026-04-06 Nacira Agram , Eya Zougar

This paper presents a novel approach to numerically solve stochastic differential games for nonlinear systems. The proposed approach relies on the nonlinear Feynman-Kac theorem that establishes a connection between parabolic deterministic…

Optimization and Control · Mathematics 2019-06-13 Ziyi Wang , Keuntaek Lee , Marcus A. Pereira , Ioannis Exarchos , Evangelos A. Theodorou

The purpose of this paper is to study 2-person zero-sum stochastic differential games, in which one player is a major one and the other player is a group of $N$ minor agents which are collectively playing, statistically identical and have…

Probability · Mathematics 2013-08-26 Rainer Buckdahn , Juan Li , Shige Peng

We propose a novel independent and payoff-based learning framework for stochastic games that is model-free, game-agnostic, and gradient-free. The learning dynamics follow a best-response-type actor-critic architecture, where agents update…

Machine Learning · Computer Science 2026-02-03 Ahmed Said Donmez , Yuksel Arslantas , Muhammed O. Sayin

Robust Markov decision processes (RMDPs) extend standard Markov decision processes (MDPs) to account for uncertainty in the transition probabilities. RMDPs have an uncertainty set that defines a set of possible transition functions, each of…

Logic in Computer Science · Computer Science 2026-04-30 Marnix Suilen , Guillermo A. Pérez