research
∙
04/19/2023
Equilibrium-Invariant Embedding, Metric Space, and Fundamental Set of 2×2 Normal-Form Games
Equilibrium solution concepts of normal-form games, such as Nash equilib...
share
research
∙
02/13/2023
Generative Adversarial Equilibrium Solvers
We introduce the use of generative adversarial learning to compute equil...
research
∙
02/01/2023
Combining Tree-Search, Generative Models, and Nash Bargaining Concepts in Game-Theoretic Reinforcement Learning
Multiagent reinforcement learning (MARL) has benefited significantly fro...
research
∙
11/17/2022
AlphaSnake: Policy Iteration on a Nondeterministic NP-hard Markov Decision Process
Reinforcement learning has recently been used to approach well-known NP-...
research
∙
10/17/2022
Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers
Solution concepts such as Nash Equilibria, Correlated Equilibria, and Co...
research
∙
10/05/2022
Game Theoretic Rating in N-player general-sum games with Equilibria
Rating strategies in a game is an important area of research in game the...
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
∙
07/29/2022
Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering
Large graphs commonly appear in social networks, knowledge graphs, recom...
research
∙
06/10/2022
The Generalized Eigenvalue Problem as a Nash Equilibrium
The generalized eigenvalue problem (GEP) is a fundamental concept in num...
research
∙
06/02/2021
Sample-based Approximation of Nash in Large Many-Player Games via Gradient Descent
Nash equilibrium is a central concept in game theory. Several Nash solve...
research
∙
02/08/2021
EigenGame Unloaded: When playing games is better than optimizing
We build on the recently proposed EigenGame that views eigendecompositio...
research
∙
10/01/2020
D3C: Reducing the Price of Anarchy in Multi-Agent Learning
Even in simple multi-agent systems, fixed incentives can lead to outcome...
research
∙
10/01/2020
EigenGame: PCA as a Nash Equilibrium
We present a novel view on principal component analysis (PCA) as a compe...
research
∙
06/08/2020
Learning to Play No-Press Diplomacy with Best Response Policy Iteration
Recent advances in deep reinforcement learning (RL) have led to consider...
research
∙
06/06/2020
Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity
In this paper, we introduce proximal gradient temporal difference learni...
research
∙
02/06/2020
Social Diversity and Social Preferences in Mixed-Motive Reinforcement Learning
Recent research on reinforcement learning in pure-conflict and pure-comm...
research
∙
08/04/2018
Global Convergence to the Equilibrium of GANs using Variational Inequalities
In optimization, the negative gradient of a function denotes the directi...
research
∙
10/19/2017
Online Monotone Games
Algorithmic game theory (AGT) focuses on the design and analysis of algo...
research
∙
11/05/2016
Generative Multi-Adversarial Networks
Generative adversarial networks (GANs) are a framework for producing a g...
research
∙
08/21/2016