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20022026
most citedA probabilistic weak formulation of mean field games and applications

181 citations · 548 across the 46 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

math.OC2019

Stochastic Graphon Games: I. The Static Case

Rene Carmona, Daniel Cooney, Christy Graves +1

We consider static finite-player network games and their continuum analogs, graphon games. Existence and uniqueness results are provided, as well as convergence of the finite-playe…

math.OC2019★ 39 cited

Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning

René Carmona, Mathieu Laurière, Zongjun Tan

We study infinite horizon discounted Mean Field Control (MFC) problems with common noise through the lens of Mean Field Markov Decision Processes (MFMDP). We allow the agents to us…

math.OC2019★ 34 cited

Linear-Quadratic Mean-Field Reinforcement Learning: Convergence of Policy Gradient Methods

René Carmona, Mathieu Laurière, Zongjun Tan

We investigate reinforcement learning in the setting of Markov decision processes for a large number of exchangeable agents interacting in a mean field manner. Applications include…

math.OC2019★ 3 cited

Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games: II -- The Finite Horizon Case

René Carmona, Mathieu Laurière

We propose two numerical methods for the optimal control of McKean-Vlasov dynamics in finite time horizon. Both methods are based on the introduction of a suitable loss function de…

q-fin.TR2019★ 1 cited

Applications of a New Self-Financing Equation

Rene Carmona, Kevin Webster

The goal of this note is to illustrate the impact of a self-financing condition recently introduced by the authors. We present the analyses of two specific applications usually con…