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#deepq-learning#deepmind#ataribreakout

Google DeepMind's Deep Q-learning playing Atari Breakout!

Two Minute Papers

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  • Recommended by 2 people: 2 in engineering communities.
  • A classic. People kept recommending it from 2016 to 2019.
  • Linked in the descriptionkuz/DeepMind-Atari-Deep-Q-Learner
  • May be out of date. Uploaded 11 years ago, in an area where tools change fast.

Beginner. No background in the topic needed.

1.4M views11 years ago2 recommendations

AI and machine learningReinforcement learningNeural networks and deep learning

A demonstration of Google DeepMind's deep reinforcement learning algorithm learning to play and master the Atari game Breakout.

Google DeepMind created an artificial intelligence program using deep reinforcement learning that plays Atari games and improves itself to a superhuman level. It is capable of playing many Atari games and uses a combination of deep artificial neural networks and reinforcement learning. After presenting their initial results with the algorithm, Google almost immediately acquired the company for several hundred million dollars, hence the name Google DeepMind. Please enjoy the footage and let me know if you have any questions regarding deep learning! ______________________ Recommended for you: 1. How DeepMind's AlphaGo Defeated Lee Sedol - youtube.com/watch?v=a-ovvd_ZrmA&index=58&list=PLujxSBD-JXgnq… 2. How DeepMind Conquered Go With Deep Learning (AlphaGo) - youtube.com/watch?v=IFmj5M5Q5jg&index=42&list=PLujxSBD-JXgnq… 3. Google DeepMind's Deep Q-Learning & Superhuman Atari Gameplays - youtube.com/watch?v=Ih8EfvOzBOY&index=14&list=PLujxSBD-JXgnq… Subscribe if you would like to see more content like this: youtube.com/subscription_center?add_user=keeroyz - Original DeepMind code: sites.google.com/a/deepmind.com/dqn/ - Ilya Kuzovkin's fork with visualization: github.com/kuz/DeepMind-Atari-Deep-Q-Learner - This patch fixes the visualization when reloading a pre-trained network. The window will appear after the first evaluation batch is done (typically a few minutes): cg.tuwien.ac.at/~zsolnai/wp/wp-content/uploads/2015/03/train… - This configuration file will run Ilya Kuzovkin's version with less than 1GB of VRAM: cg.tuwien.ac.at/~zsolnai/wp/wp-content/uploads/2015/03/run_g… - The original Nature paper on this deep learning technique is available here: nature.com/nature/journal/v518/n7540/full/nature14236.html - And some mirrors that are not behind a paywall: cs.swarthmore.edu/~meeden/cs63/s15/nature15b.pdf diyhpl.us/~nmz787/pdf/Human-level_control_through_deep_reinf… Web → cg.tuwien.ac.at/~zsolnai/ Twitter → twitter.com/karoly_zsolnai

Why it's here

2 people recommend this

What people say. Recommended as a classic demonstration of reinforcement learning in action.

u/Applepie1928in r/compsci • Recommends

On “How to start to learning AI?”

…ased on similarities, often called clustering. Requires a training set of data, but does not required labels. A good starting point would be **K-Means** or **K-Nearest-Neighbour**. * Reinforcement Learning - Used to select actions based on the state of the environment and a reward given. These models are often used to control robotics, or games ( [video ), without requiring any training data, the models "learn by doing". The best start here would be to look into **Q-Learning**. In terms of what languages and libraries to use, I would recommend Python or R as both have a good range of available tools. There are a lot of libraries out there which can make building these models easy and requ…
10View on Reddit

u/Pretentious_Usernamein r/compsci • Recommends

On “A.I. Playing NES games does surprisingly well and terribly bad.”

Yep, Here's a paper on it, and Here's a video of it playing Breakout.
1View on Reddit