Google DeepMind's Deep Q-Learning & Superhuman Atari Gameplays | Two Minute Papers
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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: http://www.nature.com/nature/journal/v518/n7540/full/nature14236.html http://www.cs.swarthmore.edu/~meeden/cs63/s15/nature15b.pdf The code is available here: https://sites.google.com/a/deepmind.com/dqn/ Ilya Kuzovkin's fork with visualization: https://github.com/kuz/DeepMind-Atari-Deep-Q-Learner This configuration file will run Ilya Kuzovkin's version with less than 1GB of VRAM: http://cg.tuwien.ac.at/~zsolnai/wp/wp-content/uploads/2015/03/run_gpu 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 Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_center?add_user=keeroyz The thumbnail was made by moparx - https://flic.kr/p/76foMV Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Patreon → https://www.patreon.com/TwoMinutePapers Facebook → https://www.facebook.com/TwoMinutePapers/ Twitter → https://twitter.com/karoly_zsolnai Web → https://cg.tuwien.ac.at/~zsolnai/
Comments
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You said in the video that it knows the score. How is that, is it being fed the score or is it watching the screen? If so, it probably has no idea what the score is, only that it's changing.
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just imagine using this for the stock market, have it research every even in government, business, all that. this could make so much money in the stock market
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You didn't describe how it all worked together, just the results.
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Bro, the 'ball behind the bricks' trick is among the oldest in the book.
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Holy shit, we've just made ourselves obsolete.
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"Whoever knows allot, but can't use it to achieve anything useful, is not an intelligent being but an encyclopaedia."
-- Károly Zsolnai-Fehér -
You didn't know that you can break them from behind??? Eh man, I did that on first try.
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I implement a Forex version at http://ai.marketcheck.co.uk/Forex let me know what you think!
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I heard they are going to try this on humanoid robots for bipedal walking.
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Is the deep Q-learning program available anywhere?
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Awesome as always!
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I also love this paper! I'm curious how far they'll be able to push this.
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