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02/13/2023
Generative Adversarial Equilibrium Solvers
We introduce the use of generative adversarial learning to compute equil...
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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...
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09/22/2022
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments
The Game Theory Multi-Agent team at DeepMind studies several aspects...
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02/21/2022
The Good Shepherd: An Oracle Agent for Mechanism Design
From social networks to traffic routing, artificial learning agents are ...
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02/21/2022
HCMD-zero: Learning Value Aligned Mechanisms from Data
Artificial learning agents are mediating a larger and larger number of i...
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01/27/2022
Human-centered mechanism design with Democratic AI
Building artificial intelligence (AI) that aligns with human values is a...
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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...
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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...
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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...
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04/16/2020
Should I tear down this wall? Optimizing social metrics by evaluating novel actions
One of the fundamental challenges of governance is deciding when and how...
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07/11/2019
A Neural Architecture for Designing Truthful and Efficient Auctions
Auctions are protocols to allocate goods to buyers who have preferences ...
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09/28/2018
Relational Forward Models for Multi-Agent Learning
The behavioral dynamics of multi-agent systems have a rich and orderly s...
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06/04/2018
Relational inductive biases, deep learning, and graph networks
Artificial intelligence (AI) has undergone a renaissance recently, makin...
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06/05/2017
Visual Interaction Networks
From just a glance, humans can make rich predictions about the future st...
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03/14/2017
Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets
The complexity of a learning task is increased by transformations in the...
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11/17/2013
Unsupervised Learning of Invariant Representations in Hierarchical Architectures
The present phase of Machine Learning is characterized by supervised lea...
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03/05/2013
