research
∙
04/26/2023
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning
We investigate whether Deep Reinforcement Learning (Deep RL) is able to ...
share
research
∙
02/13/2023
Generative Adversarial Equilibrium Solvers
We introduce the use of generative adversarial learning to compute equil...
research
∙
09/22/2022
Developing, Evaluating and Scaling Learning Agents in Multi-Agent Environments
The Game Theory Multi-Agent team at DeepMind studies several aspects...
research
∙
05/25/2021
From Motor Control to Team Play in Simulated Humanoid Football
Intelligent behaviour in the physical world exhibits structure at multip...
research
∙
12/11/2019
Biases for Emergent Communication in Multi-agent Reinforcement Learning
We study the problem of emergent communication, in which language arises...
research
∙
09/27/2019
A Generalized Training Approach for Multiagent Learning
This paper investigates a population-based training regime based on game...
research
∙
02/19/2019
Emergent Coordination Through Competition
We study the emergence of cooperative behaviors in reinforcement learnin...
research
∙
07/03/2018
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning
Recent progress in artificial intelligence through reinforcement learnin...
research
∙
06/16/2017
Value-Decomposition Networks For Cooperative Multi-Agent Learning
We study the problem of cooperative multi-agent reinforcement learning w...
research
∙
07/07/2016
Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent
We present a unifying framework for adapting the update direction in gra...
research
∙
07/29/2015
A Gauss-Newton Method for Markov Decision Processes
Approximate Newton methods are a standard optimization tool which aim to...
research
∙
05/21/2012
