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Recent techniques based on Mean Field Games (MFGs) allow the scalable analysis of multi-player games with many similar, rational agents. However, standard MFGs remain limited to homogeneous players that weakly influence each other, and…

Computer Science and Game Theory · Computer Science 2023-12-19 Kai Cui , Gökçe Dayanıklı , Mathieu Laurière , Matthieu Geist , Olivier Pietquin , Heinz Koeppl

We study analytically and by computer simulations a complex system of adaptive agents with finite memory. Borrowing the framework of the Minority Game and using the replica formalism we show the existence of an equilibrium phase transition…

Statistical Mechanics · Physics 2009-11-07 M. Marsili , R. Mulet , F. Ricci-Tersenghi , R. Zecchina

We show that equilibria of a sequential semi-anonymous nonatomic game (SSNG) can be adopted by players in corresponding large but finite dynamic games to achieve near-equilibrium payoffs. Such equilibria in the form of random…

Economics · Quantitative Finance 2016-06-23 Jian Yang

The study of learning in games typically assumes that each player always has access to all of their actions. However, in many practical scenarios, players' available actions might be restricted due to exogenous stochasticity. To model this…

Computer Science and Game Theory · Computer Science 2026-05-12 Thomas Schwarz , Ryann Sim , Chun Kai Ling

We study an ergodic mean field game problem with state constraints. In our model the agents are affected by idiosyncratic noise and use a (singular) feedback control to prevent the Brownian motion from exiting the domain. We characterize…

Analysis of PDEs · Mathematics 2023-10-05 Alessio Porretta , Michele Ricciardi

In this paper, we settle the sampling complexity of solving discounted two-player turn-based zero-sum stochastic games up to polylogarithmic factors. Given a stochastic game with discount factor $\gamma\in(0,1)$ we provide an algorithm that…

Machine Learning · Computer Science 2019-08-30 Aaron Sidford , Mengdi Wang , Lin F. Yang , Yinyu Ye

The dynamics of minority games with agents trading on different time scales is studied via dynamical mean-field theory. We analyze the case where the agents' decision-making process is deterministic and its stochastic generalization with…

Disordered Systems and Neural Networks · Physics 2009-11-10 Andrea De Martino

In this paper we consider two-person zero-sum risk-sensitive stochastic dynamic games with Borel state and action spaces and bounded reward. The term risk-sensitive refers to the fact that instead of the usual risk neutral optimization…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Ulrich Rieder

We prove that solutions to a class of Mean Field Game systems with discount are unique provided that the discount factor is large enough, and the Lagrangian term is (proportionally) small enough. This identifies an asymptotic uniqueness…

Analysis of PDEs · Mathematics 2025-10-13 Marco Cirant , Elisa Continelli

This paper analyzes a class of infinite-time-horizon stochastic games with singular controls motivated from the partially reversible problem. It provides an explicit solution for the mean-field game (MFG) and presents sensitivity analysis…

Optimization and Control · Mathematics 2020-08-12 Haoyang Cao , Xin Guo

The goal of this paper is to study the long time behavior of solutions of the first-order mean field game (MFG) systems with a control on the acceleration. The main issue for this is the lack of small time controllability of the problem,…

Optimization and Control · Mathematics 2020-07-07 Pierre Cardaliaguet , Cristian Mendico

We introduce a stochastic principal-agent model. A principal and an agent interact in a stochastic environment, each privy to observations about the state not available to the other. The principal has the power of commitment, both to elicit…

Computer Science and Game Theory · Computer Science 2024-09-13 Jiarui Gan , Rupak Majumdar , Debmalya Mandal , Goran Radanovic

Mean payoff stochastic games can be studied by means of a nonlinear spectral problem involving the Shapley operator: the ergodic equation. A solution consists in a scalar, called the ergodic constant, and a vector, called bias. The…

Optimization and Control · Mathematics 2016-05-17 Antoine Hochart

The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual Minority Game (MG)…

Trading and Market Microstructure · Quantitative Finance 2008-12-10 Antonio F. Crepaldi , Camilo Rodrigues Neto , Fernando F. Ferreira , Gerson Francisco

We investigate further several properties of the minority game we have recently introduced. We explain the origin of the phase transition and give an analytical expression of $\sigma^2/N$ in the $N\ll2^M$ region. The ability of the players…

Statistical Mechanics · Physics 2015-06-25 Damien Challet , Yi-Cheng Zhang

Mean field games (MFGs) model equilibria in games with a continuum of weakly interacting players as limiting systems of symmetric $n$-player games. We consider the finite-state, infinite-horizon problem with ergodic cost. Assuming Markovian…

Optimization and Control · Mathematics 2025-03-25 Asaf Cohen , Ethan Zell

TheMinority Game (MG) has become a paradigm to probe complex social and economical phenomena where adaptive agents compete for a limited resource, and it finds applications in statistical and nonlinear physics as well. In the traditional MG…

Adaptation and Self-Organizing Systems · Physics 2012-04-16 Zi-Gang Huang , Ji-Qiang Zhang , Jia-Qi Dong , Liang Huang , Ying-Cheng Lai

Motivated by recent developments in mean-field games in ecology, in this paper we introduce a connection between the best response dynamics in evolutionary game theory, the minimization of the highest income of a game, and minimizing…

Optimization and Control · Mathematics 2024-11-13 Dante Kalise , Alessio Oliviero , Domènec Ruiz-Balet

Stochastic min-max optimization has gained interest in the machine learning community with the advancements in GANs and adversarial training. Although game optimization is fairly well understood in the deterministic setting, some issues…

Machine Learning · Computer Science 2024-03-27 Juan Ramirez , Rohan Sukumaran , Quentin Bertrand , Gauthier Gidel

We address the problem of existence and (non-)uniqueness of solutions $\big(c,u(\cdot),\mu\big)$ to ergodic mean-field games in the whole space $\mathbb{R}^{m}$ with unbounded and merely measurable data, and for non-separable Hamiltonian.…

Analysis of PDEs · Mathematics 2023-11-09 Hicham Kouhkouh