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Research
Understanding Agent Cooperation
We employ deep multi-agent reinforcement learning to model the emergence of cooperation. The new notion of sequential social dilemmas allows us to model how rational agents interact, and arrive at...
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Research
DeepMind Papers @ NIPS (Part 3)
DeepMind Papers @ NIPS (Part 3)
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Research
DeepMind Papers @ NIPS (Part 2)
The second blog post in this series, sharing brief descriptions of the papers we are presenting at NIPS 2016 Conference in Barcelona.
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Research
Open-sourcing DeepMind Lab
DeepMind's scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how.
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Research
DeepMind Papers @ NIPS (Part 1)
Over the next three blogposts, we're going to share with you brief descriptions of the papers we are presenting at the NIPS 2016 Conference in Barcelona.
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Research
Reinforcement learning with unsupervised auxiliary tasks
Our primary mission at DeepMind is to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught how. Our reinforcement learning agents...
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Research
DeepMind and Blizzard to release StarCraft II as an AI research environment
Today at BlizzCon 2016 in Anaheim, California, we announced our collaboration with Blizzard Entertainment to open up StarCraft II to AI and Machine Learning researchers around the world.
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Research
Differentiable neural computers
In a recent study in Nature, we introduce a form of memory-augmented neural network called a differentiable neural computer, and show that it can learn to use its memory to answer questions about...
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Research
WaveNet: A generative model for raw audio
This post presents WaveNet, a deep generative model of raw audio waveforms. We show that WaveNets are able to generate speech which mimics any human voice and which sounds more natural than the...
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Research
Decoupled Neural Interfaces Using Synthetic Gradients
Neural networks are the workhorse of many of the algorithms developed at DeepMind. For example, AlphaGo uses convolutional neural networks to evaluate board positions in the game of Go and DQN and...
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Research
Deep Reinforcement Learning
Humans excel at solving a wide variety of challenging problems, from low-level motor control through to high-level cognitive tasks. Our goal at DeepMind is to create artificial agents that can...