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Research
Learning human objectives by evaluating hypothetical behaviours
When we train reinforcement learning (RL) agents in the real world, we don’t want them to explore unsafe states, such as driving a mobile robot into a ditch or writing an embarrassing email to...
AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning
AlphaStar is the first AI to reach the top league of a widely popular esport without any game restrictions. This January, a preliminary version of AlphaStar challenged two of the world's top...
Causal Bayesian Networks: A flexible tool to enable fairer machine learning
Decisions based on machine learning (ML) are potentially advantageous over human decisions, as they do not suffer from the same subjectivity, and can be more accurate and easier to analyse. At the...
Replay in biological and artificial neural networks
Our waking and sleeping lives are punctuated by fragments of recalled memories: a sudden connection in the shower between seemingly disparate thoughts, or an ill-fated choice decades ago that...
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
This paper introduces R2D3, an agent that makes efficient use of demonstrations to solve hard exploration problems in partially observable environments with highly variable initial conditions. We...
Using machine learning to accelerate ecological research
The Serengeti is one of the last remaining sites in the world that hosts an intact community of large mammals. These animals roam over vast swaths of land, some migrating thousands of miles across...
Unsupervised learning: The curious pupil
Over the last decade, machine learning has made unprecedented progress in areas as diverse as image recognition, self-driving cars and playing complex games like Go. These successes have been...
Capture the Flag: the emergence of complex cooperative agents
Mastering the strategy, tactical understanding, and team play involved in multiplayer video games represents a critical challenge for AI research. In our latest paper, now published in the journal...
Identifying and eliminating bugs in learned predictive models
Bugs and software have gone hand in hand since the beginning of computer programming. Over time, software developers have established a set of best practices for testing and debugging before...
TF-Replicator: Distributed Machine Learning for Researchers
At DeepMind, the Research Platform Team builds infrastructure to empower and accelerate our AI research. Today, we are excited to share how we developed TF-Replicator, a software library that...
Machine learning can boost the value of wind energy
Carbon-free technologies like renewable energy help combat climate change, but many of them have not reached their full potential. Consider wind power: over the past decade, wind farms have become...
AlphaStar: Mastering the real-time strategy game StarCraft II
Games have been used for decades as an important way to test and evaluate the performance of artificial intelligence systems. As capabilities have increased, the research community has sought...