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Research
Using Unity to Help Solve Intelligence
We present our use of Unity, a widely recognised and comprehensive game engine, to create more diverse, complex, virtual simulations. We describe the concepts and components developed to simplify...
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Research
Fast reinforcement learning through the composition of behaviours
Imagine if you had to learn how to chop, peel and stir all over again every time you wanted to learn a new recipe. In many machine learning systems, agents often have to learn entirely from...
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Research
Computational predictions of protein structures associated with COVID-19
The scientific community has galvanised in response to the recent COVID-19 outbreak, building on decades of basic research characterising this virus family. Labs at the forefront of the outbreak...
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Research
RL Unplugged: Benchmarks for Offline Reinforcement Learning
We propose a benchmark called RL Unplugged to evaluate and compare offline RL methods. RL Unplugged includes data from a diverse range of domains including games (e.g., Atari benchmark) and...
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Research
dm_control: Software and Tasks for Continuous Control
The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation. A MuJoCo wrapper provides convenient...
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Research
Acme: A new framework for distributed reinforcement learning
Acme is a framework for building readable, efficient, research-oriented RL algorithms. At its core Acme is designed to enable simple descriptions of RL agents that can be run at various scales of...
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Research
Using AI to predict retinal disease progression
Vision loss among the elderly is a major healthcare issue: about one in three people have some vision-reducing disease by the age of 65. Age-related macular degeneration (AMD) is the most common...
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Research
Simple Sensor Intentions for Exploration
In this paper we focus on a setting in which goal tasks are defined via simple sparse rewards, and exploration is facilitated via agent-internal auxiliary tasks. We introduce the idea of simple...
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Research
Learning to Segment Actions from Observation and Narration
We apply a generative segmental model of task structure, guided by narration, to action segmentation in video. We focus on unsupervised and weakly-supervised settings where no action labels are...
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Research
Specification gaming: the flip side of AI ingenuity
Specification gaming is a behaviour that satisfies the literal specification of an objective without achieving the intended outcome. We have all had experiences with specification gaming, even if...
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Research
Towards understanding glasses with graph neural networks
Under a microscope, a pane of window glass doesn’t look like a collection of orderly molecules, as a crystal would, but rather a jumble with no discernable structure. Glass is made by starting...
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Research
Agent57: Outperforming the human Atari benchmark
The Atari57 suite of games is a long-standing benchmark to gauge agent performance across a wide range of tasks. We’ve developed Agent57, the first deep reinforcement learning agent to obtain a...