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Two Minute Papers: Google DeepMind’s Deep Q-Learning & Superhuman Atari Gameplays | Two Minute Papers #27

Google DeepMind implemented an artificial intelligence program using deep reinforcement learning that plays Atari games and improves itself to a superhuman level. The technique is called deep Q-learning, it uses a combination of deep neural networks and reinforcement learning, and it is capable of playing many Atari games as good or better than humans. After presenting their initial results with the algorithm, Google almost immediately acquired the company for several hundred million dollars, hence the name Google DeepMind. I am sure that this is one of the biggest triumphs of deep learning, especially given the fact that now the first few successful experiments for 3D games are out there!


The Nature paper “Human-level control through deep reinforcement learning” is available here:

The code is available here:

Ilya Kuzovkin’s fork with visualization:

This configuration file will run Ilya Kuzovkin’s version with less than 1GB of VRAM:

Recommended for you:
Artificial Neural Networks and Deep Learning – https://www.youtube.com/watch?v=rCWTOOgVXyE&list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e&index=13
Recurrent Neural Network Writes Sentences About Images – https://www.youtube.com/watch?v=e-WB4lfg30M&list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e&index=15
Deep Neural Network Learns Van Gogh’s Art – https://www.youtube.com/watch?v=-R9bJGNHltQ&list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e&index=22
Terrain Traversal with Reinforcement Learning – https://www.youtube.com/watch?v=_yjHPu1aYCY&list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e&index=9

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