Learning Mean|Field Games with Discounted and Average Costs

Mean-field game theory is the study of strategic decision making by small interacting agents in very large populations. It lies at the intersection of game ...

Mean Field Games Flock! The Reinforcement Learning Way - IJCAI

Our algorithm finds a Nash Equilibrium and the agents adapt their velocity to match the neighboring flock's average one. ... Learning in mean field games: the ...

A Glimpse into the Applications of Mean Field Games

Mean field game (MFG) theory studies the strategies of agents of a large population in a competitive environment. Each agent seeks to maximise its own ...

Generalization in Mean Field Games by Learning Master Policies

Mean Field Games (MFGs) can potentially scale multi-agent systems to extremely large populations of agents. Yet, most of the literature assumes a single initial ...

Concave Utility Reinforcement Learning: the Mean-Field Game ...

Yet, this more general paradigm invalidates the classical Bellman equations, and calls for new algorithms. Mean-field Games (MFGs) are a ...

A Mean Field Game Model for Renewable Investment under Long ...

Costs, discount rate and depreciation rate. Cost evolution ... Learning in mean field games: The fictitious play. ESAIM: Control ...

Mean Field Game Theory for Gas Storage Valuation | Natixis

[29], Hadikhanloo [30] and Cardaliaguet [12] worked on learning in Mean Field Games. ... Price of anarchy for mean field games. 2018. [20] L. Clewlow and S ...

Policy Mirror Ascent for Efficient and Independent Learning in Mean ...

Markov–nash equi- libria in mean-field games with discounted cost. SIAM. Journal on Control and Optimization, 56(6):4256–4287,. 2018. 10. Page 11. Policy Mirror ...

Reinforcement Learning for Mean-Field Game - MDPI

This paper focuses on finding a mean-field equilibrium (MFE) in an action-coupled stochastic game setting in an episodic framework.

Probabilistic Analysis of Mean-Field Games

We implement the Mean-Field Game strategy developed analytically by Lasry and Lions in a purely probabilistic framework, relying on tailor-made forms of the ...

Decentralized Mean Field Games - The Intelligent Robot Learning Lab

tractable since, effectively, only two agents are being mod- elled. Lasry and Lions (2007) introduced the framework of a mean field game (MFG), which ...

Monte Carlo Simulation: What It Is, How It Works, History, 4 Key Steps

Please fill out this field. Search Search. Please fill out this field ... The geometric mean is the average of a set of products, the calculation of ...

Reinforcement Learning for Mean Field Games and ... - eScholarship

His influence on my studies started during a seminar in Mean Field. Games when I was a student at the University of Milan. The passion and pride shown for his ...

René Carmona: Mean field games with major and minor players

Comments · Peter Imkeller: An introduction to BSDE · Pierre Cardaliaguet: Mean Field Games - Lecture 1 · Niao He - Reinforcement Learning in Mean ...

Mean‐field games with differing beliefs for algorithmic trading

We analyze the mean-field game (MFG) limit of the stochastic game and show that the Nash equilibrium is given by the solution to a nonstandard ...

Applications of Mean Field Games - IMSI institute

The paradigm of Mean Field Games (MFG) has become a major connection between distributed decision-making and stochastic modeling.

A General Theory for Discrete-Time Mean-Field Games - UCLA

mean-field games with discounted cost," SICON, 56(6):4256-4287, 2018. ▻ —- “Approximate Nash Equilibria in partially observed stochastic games.

Discrete mean field games: Existence of equilibria and convergence

We prove the existence of a mean field equilibrium assuming continuity of the cost and of the drift. These conditions are more general than the existing papers ...

Approximate Nash Equilibria in Partially Observed Stochastic ...

In this paper, we consider discrete-time partially observed mean-field games with infinite-horizon discounted-cost criteria.

Discrete Mean Field Games: Existence of Equilibria and Convergence

We define the notion of mean field equilibrium for the finite horizon case as in the discounted case, by replacing the cost function (5) by (18) ...