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Two-sided matchings are an important theoretical tool used to model markets and social interactions. In many real life problems the utility of an agent is influenced not only by their own choices, but also by the choices that other agents…

Computer Science and Game Theory · Computer Science 2012-07-17 Simina Brânzei , Tomasz P. Michalak , Talal Rahwan , Kate Larson , Nicholas R. Jennings

We study a mathematical model for revenue management under competition with multiple sellers. The model combines the stochastic knapsack problem, a classic revenue management model, with a non coorperative game model that characterizes the…

Optimization and Control · Mathematics 2019-09-11 Yingdong Lu

We consider the issue of a market maker acting at the same time in the lit and dark pools of an exchange. The exchange wishes to establish a suitable make-take fees policy to attract transactions on its venues. We first solve the stochastic…

Mathematical Finance · Quantitative Finance 2019-12-04 Bastien Baldacci , Iuliia Manziuk , Thibaut Mastrolia , Mathieu Rosenbaum

This paper builds on the work of Degond, Herty and Liu by considering N-player stochastic differential games. The control corresponding to a Nash equilibrium of such a game is approximated through model predictive control (MPC) techniques.…

Optimization and Control · Mathematics 2019-11-12 Matt Barker

Today's multiagent systems have grown too complex to rely on centralized controllers, prompting increasing interest in the design of distributed algorithms. In this respect, game theory has emerged as a valuable tool to complement more…

Systems and Control · Computer Science 2020-02-19 Rahul Chandan , Dario Paccagnan , Jason R. Marden

Pricing decisions stand out as one of the most critical tasks a company faces, particularly in today's digital economy. As with other business decision-making problems, pricing unfolds in a highly competitive and uncertain environment.…

Computer Science and Game Theory · Computer Science 2024-09-04 Daniel García Rasines , Roi Naveiro , David Ríos Insua , Simón Rodríguez Santana

Matching markets are of particular interest in computer science and economics literature as they are often used to model real-world phenomena where we aim to equitably distribute a limited amount of resources to multiple agents and…

Computer Science and Game Theory · Computer Science 2021-10-01 Andrew Yang , Bruce Changlong Xu , Ivan Villa-Renteria

We characterize zonal ancillary market coupling relying on noncooperative game theory. To that purpose, we formulate the ancillary market as a multi-leader single follower bilevel problem, that we subsequently cast as a generalized Nash…

Multiagent Systems · Computer Science 2025-11-13 Francesco Morri , Hélène Le Cadre , Pierre Gruet , Luce Brotcorne

Consider discrete-time linear distributed averaging dynamics, whereby agents in a network start with uncorrelated and unbiased noisy measurements of a common underlying parameter (state of the world) and iteratively update their estimates…

Optimization and Control · Mathematics 2023-03-21 Giacomo Como , Fabio Fagnani , Anton V. Proskurnikov

Stochastic games are a popular framework for studying multi-agent reinforcement learning (MARL). Recent advances in MARL have focused primarily on games with finitely many states. In this work, we study multi-agent learning in stochastic…

Machine Learning · Computer Science 2024-03-28 Awni Altabaa , Bora Yongacoglu , Serdar Yüksel

Distributed model predictive control (MPC) is either cooperative or competitive, and control-theoretic properties have been less studied in the competitive (e.g., game theory) setting. This paper studies MPC with linear dynamics and a…

Optimization and Control · Mathematics 2017-09-27 Yonatan Mintz , John Audie Cabrera , Jhoanna Rhodette Pedrasa , Anil Aswani

We introduce a simple benchmark model of dynamic matching in networked markets, where agents arrive and depart stochastically and the network of acceptable transactions among agents forms a random graph. We analyze our model from three…

Computer Science and Game Theory · Computer Science 2014-02-18 Mohammad Akbarpour , Shengwu Li , Shayan Oveis Gharan

Mean field games are studied by means of the weak formulation of stochastic optimal control. This approach allows the mean field interactions to enter through both state and control processes and take a form which is general enough to…

Probability · Mathematics 2015-04-09 Rene Carmona , Daniel Lacker

We introduce a class of robust control problems formulated in min-max form, in which the principal agent is viewed as a central planner facing Nature. The agent's cost is a nonlinear function of all its possible realizations, encompassing…

Optimization and Control · Mathematics 2026-04-24 François Delarue , Pierre Lavigne

The present paper provides a study of high-dimensional statistical arbitrage that combines factor models with the tools from stochastic control, obtaining closed-form optimal strategies which are both interpretable and computationally…

Mathematical Finance · Quantitative Finance 2021-06-25 Jorge Guijarro-Ordonez

Markov games with coupling constraints model constrained dynamical decision-making involving self-interested agents, where the feasibility of an individual agent's strategy depends on the joint strategies of the others. Such games arise in…

Computer Science and Game Theory · Computer Science 2026-05-27 Tingting Ni , Anna Maddux , Maryam Kamgarpour

This paper considers mean field games in a multi-agent Markov decision process (MDP) framework. Each player has a continuum state and binary action, and benefits from the improvement of the condition of the overall population. Based on an…

Optimization and Control · Mathematics 2021-01-05 Minyi Huang , Yan Ma

Macroscopic properties of equity markets affect the performance of active equity strategies but many are not adequately captured by conventional models of financial mathematics and econometrics. Using the CRSP Database of the US equity…

Statistical Finance · Quantitative Finance 2025-04-07 Steven Campbell , Qien Song , Ting-Kam Leonard Wong

We study a class of stochastic dynamic games that exhibit strategic complementarities between players; formally, in the games we consider, the payoff of a player has increasing differences between her own state and the empirical…

Computer Science and Game Theory · Computer Science 2010-12-13 Sachin Adlakha , Ramesh Johari

In this paper, I introduce a profit-maximizing centralized marketplace into a decentralized market with search frictions. Agents choose between the centralized marketplace and the decentralized bilateral trade. I characterize the optimal…

Theoretical Economics · Economics 2021-11-29 Berk Idem