# Replicating-DeepMind

**Repository Path**: jmche/Replicating-DeepMind

## Basic Information

- **Project Name**: Replicating-DeepMind
- **Description**: Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind
- **Primary Language**: C++
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-26
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

Replicating-DeepMind
====================

Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind. All the information is in our [Wiki](https://github.com/kristjankorjus/Replicating-DeepMind/wiki).

**Progress:** System is up and running on a GPU cluster with cuda-convnet2. It can learn to play better than random but not much better yet :) It is rather fast but still about 2x slower than DeepMind's original system. It does not have RMSprop implemented at the moment which is our next goal. 

Note 1: You can also check out a popular science article we wrote about the system to [Robohub](http://robohub.org/artificial-general-intelligence-that-plays-atari-video-games-how-did-deepmind-do-it/).

Note 2: Nathan Sprague has a implementation based on Theano. It can do fairly well. See [his github](https://github.com/spragunr/deep_q_rl) for more details.