Matrix games like Prisoner's Dilemma have guided research on social dilemmas for decades.
However, they necessarily treat the choice to cooperate or defect as an atomic action. In …

Deep reinforcement learning agents have achieved state-of-the-art results by directly
maximising cumulative reward. However, environments contain a much wider variety of possible …

Reinforcement learning (RL) has shown great success in increasingly complex single-agent
environments and two-player turn-based games. However, the real world contains multiple …

Over the past 20 years, neuroscience research on reward-based learning has converged
on a canonical model, under which the neurotransmitter dopamine ‘stamps in’associations …

We study the problem of cooperative multi-agent reinforcement learning with a single joint
reward signal. This class of learning problems is difficult because of the often large combined …

In recent years deep reinforcement learning (RL) systems have attained superhuman
performance in a number of challenging task domains. However, a major limitation of such …

DeepMind Lab is a first-person 3D game platform designed for research and development of
general artificial intelligence and machine learning systems. DeepMind Lab can be used to …

We propose a unified mechanism for achieving coordination and communication in Multi-Agent
Reinforcement Learning (MARL), through rewarding agents for having causal influence …

Problems of cooperation--in which agents seek ways to jointly improve their welfare--are
ubiquitous and important. They can be found at scales ranging from our daily routines--such as …

The human visual system can rapidly recognize objects despite transformations that alter
their appearance. The precise timing of when the brain computes neural representations that …