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This article considers the average optimality for a continuous-time Markov decision process with Borel state and action spaces and an arbitrarily unbounded nonnegative cost rate. The existence of a deterministic stationary optimal policy is…

Optimization and Control · Mathematics 2014-03-05 Yi Zhang

In this paper we consider stopping problems for continuous-time Markov chains under a general risk-sensitive optimization criterion for problems with finite and infinite time horizon. More precisely our aim is to maximize the certainty…

Probability · Mathematics 2019-07-05 Nicole Bäuerle , Anton Popp

We construct a saddle point in a class of zero-sum games between a stopper and a singular-controller. The underlying dynamics is a one-dimensional, time-homogeneous, singularly controlled diffusion taking values either on $\mathbb{R}$ or on…

Optimization and Control · Mathematics 2024-10-28 Andrea Bovo , Tiziano De Angelis

In this paper we study the nonzero-sum Dynkin game in continuous time which is a two player non-cooperative game on stopping times. We show that it has a Nash equilibrium point for general stochastic processes. As an application, we…

Pricing of Securities · Quantitative Finance 2008-12-10 Said Hamadene , Jianfeng Zhang

This paper concerns discrete-time infinite-horizon stochastic control systems with Borel state and action spaces and universally measurable policies. We study optimization problems on strategic measures induced by the policies in these…

Optimization and Control · Mathematics 2023-12-22 Huizhen Yu

We consider a non-cooperative constrained stochastic games with N players with the following special structure. With each player there is an associated controlled Markov chain. The transition probabilities of the i-th Markov chain depend…

Information Theory · Computer Science 2007-07-13 E. Altman , K. Avrachenkov , N. Bonneau , M. Debbah , R. El-Azouzi , D. Sadoc Menasche

This paper considers a class of reinforcement-based learning (namely, perturbed learning automata) and provides a stochastic-stability analysis in repeatedly-played, positive-utility, finite strategic-form games. Prior work in this class of…

Computer Science and Game Theory · Computer Science 2019-01-29 Georgios C. Chasparis

In this work, we investigate a security game between an attacker and a defender, originally proposed in \cite{emadi2019security}. As is well known, the combinatorial nature of security games leads to a large cost matrix. Therefore,…

Computer Science and Game Theory · Computer Science 2020-07-30 HAmid Emadi , Sourabh Bhattacharya

We prove that every two-player nonzero-sum stopping game in discrete time admits an \epsilon-equilibrium in randomized strategies for every \epsilon >0. We use a stochastic variation of Ramsey's theorem, which enables us to reduce the…

Probability · Mathematics 2007-05-23 Eran Shmaya , Eilon Solan

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 large family of discrete and continuous time controlled Markov processes and study an ergodic risk-sensitive minimization problem. Under a blanket stability assumption, we provide a complete analysis to this problem. In…

Optimization and Control · Mathematics 2022-07-18 Anup Biswas , Somnath Pradhan

We address payoff-based decentralized learning in infinite-horizon zero-sum Markov games. In this setting, each player makes decisions based solely on received rewards, without observing the opponent's strategy or actions nor sharing…

Computer Science and Game Theory · Computer Science 2025-02-11 Reda Ouhamma , Maryam Kamgarpour

The mathematical characterization of social-distancing games in classical epidemic theory remains an important question, for their applications to both infectious-disease theory and memetic theory. We consider a special case of the dynamic…

Computer Science and Game Theory · Computer Science 2026-03-16 Connor D Olson , Timothy C Reluga

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

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

In the paper we consider the controlled continuous-time Markov chain describing the interacting particles system with the finite number of types. The system is controlled by two players with the opposite purposes. The limiting game as the…

Optimization and Control · Mathematics 2014-12-02 Yurii Averboukh

In this paper, we consider risk-sensitive discounted control problem for continuous-time jump Markov processes taking values in general state space. The transition rates of underlying continuous-time jump Markov processes and the cost rates…

Optimization and Control · Mathematics 2021-04-27 Chandan Pal , Subrata Golui

A zero-sum two-person Perfect Information Semi-Markov game (PISMG) under limiting ratio average payoff has a value and both the maximiser and the minimiser have optimal pure semi-stationary strategies. We arrive at the result by first…

Computer Science and Game Theory · Computer Science 2023-02-15 S. Sinha , K. G. Bakshi

In this paper, we consider discrete-time partially observed mean-field games with the risk-sensitive optimality criterion. We introduce risk-sensitivity behaviour for each agent via an exponential utility function. In the game model, each…

Systems and Control · Electrical Eng. & Systems 2022-11-11 Naci Saldi , Tamer Basar , Maxim Raginsky

We consider robust Markov Decision Processes with Borel state and action spaces, unbounded cost and finite time horizon. Our formulation leads to a Stackelberg game against nature. Under integrability, continuity and compactness assumptions…

Optimization and Control · Mathematics 2025-10-16 Nicole Bäuerle , Alexander Glauner
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