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A mean-field game (MFG) seeks the Nash Equilibrium of a game involving a continuum of players, where the Nash Equilibrium corresponds to a fixed point of the best-response mapping. However, simple fixed-point iterations do not always…

Optimization and Control · Mathematics 2025-07-15 Jiajia Yu , Xiuyuan Cheng , Jian-Guo Liu , Hongkai Zhao

In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always…

Computer Science and Game Theory · Computer Science 2012-09-17 Yaron Velner , Krishnendu Chatterjee , Laurent Doyen , Thomas A. Henzinger , Alexander Rabinovich , Jean-Francois Raskin

Two-player quantitative zero-sum games provide a natural framework to synthesize controllers with performance guarantees for reactive systems within an uncontrollable environment. Classical settings include mean-payoff games, where the…

Logic in Computer Science · Computer Science 2016-07-11 Patricia Bouyer , Nicolas Markey , Mickael Randour , Kim G. Larsen , Simon Laursen

We apply a convexification-based numerical method to forecast public sentiment dynamics using Mean Field Games (MFGs). The theoretical foundation for the convexification approach, established in our prior work, guarantees global convergence…

Numerical Analysis · Mathematics 2026-04-22 Shi Chen , Michael V. Klibanov , Kevin McGoff , Trung Truong , Wangjiaxuan Xin , Shuhua Yin

Reinforcement learning is a powerful tool to learn the optimal policy of possibly multiple agents by interacting with the environment. As the number of agents grow to be very large, the system can be approximated by a mean-field problem.…

Optimization and Control · Mathematics 2020-08-18 Weichen Wang , Jiequn Han , Zhuoran Yang , Zhaoran Wang

Multiagent reinforcement learning algorithms have not been widely adopted in large scale environments with many agents as they often scale poorly with the number of agents. Using mean field theory to aggregate agents has been proposed as a…

Multiagent Systems · Computer Science 2022-04-14 Sriram Ganapathi Subramanian , Matthew E. Taylor , Mark Crowley , Pascal Poupart

We consider the problem of representing collective behavior of large populations and predicting the evolution of a population distribution over a discrete state space. A discrete time mean field game (MFG) is motivated as an interpretable…

Machine Learning · Computer Science 2018-04-24 Jiachen Yang , Xiaojing Ye , Rakshit Trivedi , Huan Xu , Hongyuan Zha

Mobile crowdsensing (MCS) is a new paradigm of sensing by taking advantage of the rich embedded sensors of mobile user devices. However, the traditional server-client MCS architecture often suffers from the high operational cost on the…

Computer Science and Game Theory · Computer Science 2017-05-16 Changkun Jiang , Lin Gao , Lingjie Duan , Jianwei Huang

We consider network aggregative games to model and study multi-agent populations in which each rational agent is influenced by the aggregate behavior of its neighbors, as specified by an underlying network. Specifically, we examine systems…

Systems and Control · Computer Science 2015-06-26 Francesca Parise , Sergio Grammatico , Basilio Gentile , John Lygeros

Two-player games on graphs is central in many problems in formal verification and program analysis such as synthesis and verification of open systems. In this work we consider solving recursive game graphs (or pushdown game graphs) that can…

Logic in Computer Science · Computer Science 2016-05-17 Krishnendu Chatterjee , Yaron Velner

Mean-field games (MFG) were introduced to efficiently analyze approximate Nash equilibria in large population settings. In this work, we consider entropy-regularized mean-field games with a finite state-action space in a discrete time…

Computer Science and Game Theory · Computer Science 2022-07-26 Yue Guan , Mi Zhou , Ali Pakniyat , Panagiotis Tsiotras

Mean-Field Games are games with a continuum of players that incorporate the time-dimension through a control-theoretic approach. Recently, simpler approaches relying on the Best Reply Strategy have been proposed. They assume that the agents…

Optimization and Control · Mathematics 2014-12-24 Pierre Degond , Michael Herty , Jian-Guo Liu

The convexification numerical method with the rigorously established global convergence property is constructed for a problem for the Mean Field Games System of the second order. This is the problem of the retrospective analysis of a game…

Numerical Analysis · Mathematics 2023-06-30 Michael V. Klibanov , Jingzhi Li , Zhipeng Yang

The standard solution concept for stochastic games is Markov perfect equilibrium (MPE); however, its computation becomes intractable as the number of players increases. Instead, we consider mean field equilibrium (MFE) that has been…

Theoretical Economics · Economics 2020-06-05 Bar Light , Gabriel Weintraub

In this paper we formulate the now classical problem of optimal liquidation (or optimal trading) inside a Mean Field Game (MFG). This is a noticeable change since usually mathematical frameworks focus on one large trader in front of a…

Trading and Market Microstructure · Quantitative Finance 2017-09-22 Pierre Cardaliaguet , Charles-Albert Lehalle

High performance machine learning models have become highly dependent on the availability of large quantity and quality of training data. To achieve this, various central agencies such as the government have suggested for different data…

Machine Learning · Computer Science 2019-11-27 Zhiliang Chen

Hyperinflation and price volatility in virtual economies has the potential to reduce player satisfaction and decrease developer revenue. This paper describes intuitive analytical methods for monitoring volatility and inflation in virtual…

General Finance · Quantitative Finance 2019-06-19 Oliver James Scholten , Peter Cowling , Kenneth A. Hawick , James Alfred Walker

We study discounted infinitely repeated games in which players agree on a cooperative mixed action profile but, at each step, observe only the realized pure actions. This form of imperfect monitoring breaks classical trigger strategies,…

Applications · Statistics 2026-03-09 Aymeric Capitaine , Antoine Scheid , Etienne Boursier , Alain Durmus , Michael I. Jordan

The emergence of mobile games has caused a paradigm shift in the video-game industry. Game developers now have at their disposal a plethora of information on their players, and thus can take advantage of reliable models that can accurately…

Machine Learning · Statistics 2018-11-29 Paul Bertens , Anna Guitart , África Periáñez

The main objective of higher education is to provide quality education to students. One way to achieve highest level of quality in higher education system is by discovering knowledge for prediction regarding enrolment of students in a…

Machine Learning · Computer Science 2012-03-19 Surjeet Kumar Yadav , Brijesh Bharadwaj , Saurabh Pal
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