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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...
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08/27/2020
The Advantage Regret-Matching Actor-Critic
Regret minimization has played a key role in online learning, equilibriu...
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05/04/2020
Navigating the Landscape of Multiplayer Games to Probe the Drosophila of AI
Multiplayer games have a long history in being used as key testbeds for ...
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06/01/2019
Neural Replicator Dynamics
In multiagent learning, agents interact in inherently nonstationary envi...
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01/24/2018
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents
Psychlab is a simulated psychology laboratory inside the first-person 3D...
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11/02/2017
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
To achieve general intelligence, agents must learn how to interact with ...
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06/16/2017
Value-Decomposition Networks For Cooperative Multi-Agent Learning
We study the problem of cooperative multi-agent reinforcement learning w...
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04/15/2017
The Reactor: A Sample-Efficient Actor-Critic Architecture
In this work we present a new reinforcement learning agent, called React...
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04/12/2017
Deep Q-learning from Demonstrations
Deep reinforcement learning (RL) has achieved several high profile succe...
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06/10/2016
