Description
Back to topMulti-agent reinforcement learning (MARL) with incorporation of techniques and ideas from the theory of mean field games is one of the most active areas in learning and control. The purpose of this workshop is to bring leading experts and junior researchers to showcase the latest developments in this interdisciplinary field.
Organizer
Back to topSpeakers
Back to topSchedule
Back to topSpeaker: Xunyu Zhou (Columbia University)
Speaker: Josef Teichmann (ETH Zürich)
Speaker: Mathieu Rosenbaum (Ecole Polytechnique)
Speaker: Huyên Pham (University of Paris 6 and CNRS)
Speaker: Yufei Zhang (London School of Economics and Political Science)
Speaker: Ruimeng Hu (University of California, Santa Barbara)
Speaker: Rama Cont (University of Oxford)
Speaker: Sebastian Jaimungal (University of Toronto)
Speaker: Thibaut Mastrolia (University of California, Berkeley (UC Berkeley))
Speaker: Martin Larsson (Carnegie-Mellon University)
Speaker: Johannes Ruf (London School of Economics)
Speaker: Renyuan Xu (University of Southern California)
Speaker: Camilo A Garcia Trillos (University College London)
Speaker: Wenpin Tang (Columbia University)
Speaker: Olivier Gueant (Université Paris 1 Pantheon Sorbonne)
Speaker: Christa Cuchiero (University of Vienna)
Speaker: Lukas Szpruch (University of Edinburgh)
Speaker: Zhenjie Ren (University Paris Dauphine – PSL)
Speaker: Sarah Perrin (Université de Lille)
Speaker: Anran Hu (University of California, Berkeley (UC Berkeley))
Speaker: Siting Liu (University of California, Los Angeles (UCLA))
Speaker: Jiacheng Zhang (University of California, Berkeley (UC Berkeley))
Speaker: Daniel Lacker (Columbia University)
Speaker: Beatrice Acciaio (ETH Zürich)
Speaker: Jean-Pierre Fouque (University of California, Santa Barbara (UCSB))
Speaker: Haoyang Cao (The Alan Turing Institute)
Speaker: Mathieu Lauriere (NYU Shanghai)
Speaker: Rene Carmona (Princeton University)
Videos
Back to top
Policy Gradient is Essentially Policy Evaluation
Xunyu Zhou
May 23, 2022
Optimal Stopping via Randomized Neural Networks
Josef Teichmann
May 23, 2022
Market making and incentives design in the presence of a dark pool: a deep reinforcement learning approach
Mathieu Rosenbaum
May 23, 2022
Policy gradients algorithms for mean-field control in continuous time
Huyên Pham
May 23, 2022
From stochastic control to continuous-time reinforcement learning
Yufei Zhang
May 23, 2022
Convergence of Empirical Measures, Mean-Field Games and Deep Learning Algorithms
Ruimeng Hu
May 23, 2022
Dynamics of Market Making Algorithms in Dealer Markets: Learning and Tacit Collusion
Rama Cont
May 23, 2022
Deep Learning for Principal-Agent Mean Field Games
Sebastian Jaimungal
May 24, 2022
Agency problem with mean field agents
Thibaut Mastrolia
May 24, 2022
Propagation of chaos for maxima of particle systems with mean-field drift interaction
Martin Larsson
May 24, 2022
Minimum curvature flow and martingale exit times
Johannes Ruf
May 24, 2022
System Noise and Individual Exploration in Learning Large Population Games
Renyuan Xu
May 24, 2022
DISTRIBUTIONALLY ROBUST LEARNING OVER DEEP NEURAL NETWORKS AND THEIR ASSOCIATED REGULARIZED RISK
Camilo A Garcia Trillos
May 24, 2022
Some stories about Brownian interacting systems with absorption
Wenpin Tang
May 24, 2022
Market making algorithms: the next success of Reinforcement Learning?
Olivier Gueant
May 25, 2022
Optimal bailout strategies resulting from the drift controlled supercooled Stefan problem
Christa Cuchiero
May 25, 2022
Exploration-exploitation trade-off for continuous-time episodic reinforcement learning
Lukas Szpruch
May 25, 2022
Mean Field Optimization regularized by Fisher Information
Zhenjie Ren
May 25, 2022
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
Sarah Perrin
May 25, 2022
An Optimization Framework for Solving Mean-Field Games
Anran Hu
May 25, 2022
Controlling the propagation of epidemics via mean-field control
Siting Liu
May 25, 2022
Sensitivity and Robustness of Stackelberg Mean-Field Games through an Optimization Lense
Jiacheng Zhang
May 25, 2022
Mean field approximations via log-concavity, and a non-asymptotic perspective on mean field control
Daniel Lacker
May 26, 2022
Reinforcement Learning Algorithm for Mixed Mean Field Control Games
Jean-Pierre Fouque
May 26, 2022
Assessing Transfer Learning
Haoyang Cao
May 26, 2022
An Overview of Learning Mean Field Games
Mathieu Lauriere
May 26, 2022
Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning
Rene Carmona
May 26, 2022