research
∙
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...
share
research
∙
05/13/2022
Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning
Advances in artificial intelligence often stem from the development of n...
research
∙
02/07/2022
Reward-Respecting Subtasks for Model-Based Reinforcement Learning
To achieve the ambitious goals of artificial intelligence, reinforcement...
research
∙
12/06/2021
Player of Games
Games have a long history of serving as a benchmark for progress in arti...
research
∙
01/11/2021
Solving Common-Payoff Games with Approximate Policy Iteration
For artificially intelligent learning systems to have widespread applica...
research
∙
08/27/2020
The Advantage Regret-Matching Actor-Critic
Regret minimization has played a key role in online learning, equilibriu...
research
∙
04/20/2020
Approximate exploitability: Learning a best response in large games
A common metric in games of imperfect information is exploitability, i.e...
research
∙
08/26/2019
OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in...
research
∙
03/13/2019