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03/02/2023
Learning not to Regret
Regret minimization is a key component of many algorithms for finding Na...
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12/06/2021
Player of Games
Games have a long history of serving as a benchmark for progress in arti...
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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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04/20/2020
Approximate exploitability: Learning a best response in large games
A common metric in games of imperfect information is exploitability, i.e...
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08/26/2019
OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in...
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06/01/2019
Neural Replicator Dynamics
In multiagent learning, agents interact in inherently nonstationary envi...
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03/02/2019
Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research
Evolution has produced a multi-scale mosaic of interacting adaptive unit...
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04/11/2018
Emergent Communication through Negotiation
Multi-agent reinforcement learning offers a way to study how communicati...
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12/05/2017
