research
∙
02/13/2023
Generative Adversarial Equilibrium Solvers
We introduce the use of generative adversarial learning to compute equil...
share
research
∙
09/22/2022
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments
The Game Theory Multi-Agent team at DeepMind studies several aspects...
research
∙
08/22/2022
Learning Correlated Equilibria in Mean-Field Games
The designs of many large-scale systems today, from traffic routing envi...
research
∙
06/30/2022
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning
We introduce DeepNash, an autonomous agent capable of learning to play t...
research
∙
12/17/2021
An overview of active learning methods for insurance with fairness appreciation
This paper addresses and solves some challenges in the adoption of machi...
research
∙
11/16/2021
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO
Recent advances in multiagent learning have seen the introduction ofa fa...
research
∙
10/22/2021
Solving N-player dynamic routing games with congestion: a mean field approach
The recent emergence of navigational tools has changed traffic patterns ...
research
∙
09/28/2021
Fairness guarantee in multi-class classification
Algorithmic Fairness is an established area of machine learning, willing...
research
∙
09/20/2021
Generalization in Mean Field Games by Learning Master Policies
Mean Field Games (MFGs) can potentially scale multi-agent systems to ext...
research
∙
06/28/2021
Evolutionary Dynamics and Φ-Regret Minimization in Games
Regret has been established as a foundational concept in online learning...
research
∙
06/08/2021
Time-series Imputation of Temporally-occluded Multiagent Trajectories
In multiagent environments, several decision-making individuals interact...
research
∙
06/07/2021
Concave Utility Reinforcement Learning: the Mean-field Game viewpoint
Concave Utility Reinforcement Learning (CURL) extends RL from linear to ...
research
∙
05/17/2021
Mean Field Games Flock! The Reinforcement Learning Way
We present a method enabling a large number of agents to learn how to fl...
research
∙
02/28/2021
Scaling up Mean Field Games with Online Mirror Descent
We address scaling up equilibrium computation in Mean Field Games (MFGs)...
research
∙
02/10/2021
Conditional Versus Adversarial Euler-based Generators For Time Series
We introduce new generative models for time series based on Euler discre...
research
∙
11/18/2020
Game Plan: What AI can do for Football, and What Football can do for AI
The rapid progress in artificial intelligence (AI) and machine learning ...
research
∙
07/05/2020
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
In this paper, we deepen the analysis of continuous time Fictitious Play...
research
∙
03/22/2020
Reinforcement Learning in Economics and Finance
Reinforcement learning algorithms describe how an agent can learn an opt...
research
∙
07/04/2019