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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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05/12/2022
A Generalist Agent
Inspired by progress in large-scale language modeling, we apply a simila...
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02/08/2022
Competition-Level Code Generation with AlphaCode
Programming is a powerful and ubiquitous problem-solving tool. Developin...
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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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11/28/2020
Human-Agent Cooperation in Bridge Bidding
We introduce a human-compatible reinforcement-learning approach to a coo...
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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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02/27/2020
Learning to Resolve Alliance Dilemmas in Many-Player Zero-Sum Games
Zero-sum games have long guided artificial intelligence research, since ...
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12/11/2019
Biases for Emergent Communication in Multi-agent Reinforcement Learning
We study the problem of emergent communication, in which language arises...
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03/19/2019
Learning Reciprocity in Complex Sequential Social Dilemmas
Reciprocity is an important feature of human social interaction and unde...
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01/11/2019
An investigation of model-free planning
The field of reinforcement learning (RL) is facing increasingly challeng...
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08/20/2018