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spragunr
deep_q_rl
Python2015–2015
spragunr / deep_q_rl

deep_q_rl

Theano-based implementation of Deep Q-learning

Learning & Reference
Explore on GitHubRead Hacker News discussions
3Distinct people
3Mentions
0Explicit recommenders
1.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Theano-based implementation of Deep Q-learning

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month3 dated mentions

Observed mentions: 2015-01-04 01:26:54 UTC to 2015-12-25 05:37:53 UTC.

012015-01-01 00:00:00 UTC to 2015-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 20152015-02-01 00:00:00 UTC to 2015-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-03-01 00:00:00 UTC to 2015-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2015-04-01 00:00:00 UTC to 2015-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-05-01 00:00:00 UTC to 2015-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-06-01 00:00:00 UTC to 2015-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJun 20152015-07-01 00:00:00 UTC to 2015-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-08-01 00:00:00 UTC to 2015-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-09-01 00:00:00 UTC to 2015-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-10-01 00:00:00 UTC to 2015-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-11-01 00:00:00 UTC to 2015-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-12-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsDec 2015

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jan 20152015-01-01 00:00:00 UTC2015-02-01 00:00:00 UTC101
Feb 20152015-02-01 00:00:00 UTC2015-03-01 00:00:00 UTC000
Mar 20152015-03-01 00:00:00 UTC2015-04-01 00:00:00 UTC101
Apr 20152015-04-01 00:00:00 UTC2015-05-01 00:00:00 UTC000
May 20152015-05-01 00:00:00 UTC2015-06-01 00:00:00 UTC000
Jun 20152015-06-01 00:00:00 UTC2015-07-01 00:00:00 UTC000
Jul 20152015-07-01 00:00:00 UTC2015-08-01 00:00:00 UTC000
Aug 20152015-08-01 00:00:00 UTC2015-09-01 00:00:00 UTC000
Sep 20152015-09-01 00:00:00 UTC2015-10-01 00:00:00 UTC000
Oct 20152015-10-01 00:00:00 UTC2015-11-01 00:00:00 UTC000
Nov 20152015-11-01 00:00:00 UTC2015-12-01 00:00:00 UTC000
Dec 20152015-12-01 00:00:00 UTC2016-01-01 00:00:00 UTC101

What Hacker News says

3 sources
smhx·Dec 25, 2015
I didn't mean it in a condescending way. I was stating that this is not algorithmically new, and is a reproduction of the paper. From the README of the repository, it is not obvious that this is a reproduction. The information is fairly hidden, and the DQN paper is given as a reference. A casual glance might suggest that there is research innovation there. Here are other reproductions just FYI: Original Torch version from DeepMind: [github mirror] https://github.com/kuz/DeepMind-Atari-Deep-Q-Learner Caffe: https://github.com/muupan/dqn-in-the-caffe Theano: https://github.com/spragunr/deep_q_rl Neon: https://github.com/DoctorTeeth/dqn
In I Trained a Deep Q Network Built in TensorFlow to Play Atari Pong
albertzeyer·Mar 29, 2015
I know some more. Some of them are made as libraries, some are just code examples, where you however could extract out some relevant code. * PyLearn, LISA labs, http://deeplearning.net/software/pylearn2/ * LSTM, http://deeplearning.net/tutorial/lstm.html#lstm * LSTM, https://github.com/skaae/nntools * LSTM, https://github.com/JonathanRaiman/theano_lstm * LSTM, https://github.com/mohammadpz/Recurrent-Neural-Networks * LSTM, http://christianherta.de/lehre/dataScience/machineLearning/n... * LSTM, https://gist.github.com/jpuigcerver/9358036 * LSTM + CTC, https://github.com/kastnerkyle/net * Speech modeling, LSTM, https://github.com/kastnerkyle/speech_density * FF + RNN, https://github.com/lmjohns3/theano-nets * FF + RNN, https://github.com/lmjohns3/theanets Speech: https://github.com/lmjohns3/arrnn-experiment/blob/master/tas... * FF, https://
Read the rest
github.com/benanne/Lasagne * RNN, https://github.com/pascanur/trainingRNNs * RNN, https://github.com/pascanur/GroundHog (Razvan Pascanu, KyungHyun Cho, Caglar Gulcehre) * RNN + CTC, https://github.com/shawntan/rnn-experiment (Shawn Tan) * RNN + CTC, https://github.com/shawntan/theano-ctc (Shawn Tan) * RNN + CTC, https://github.com/rakeshvar/rnn_ctc * RNN + CTC, OCR, https://github.com/rakeshvar/chamanti_ocr, https://github.com/rakeshvar/chamanti3_ocr * RNN, https://github.com/gwtaylor/theano-rnn * LSTM, RBM, DBN, https://github.com/kratarth1203/NeuralNet * RBM, https://github.com/benanne/morb * Q-learning, https://github.com/spragunr/deep_q_rl * Deep Generative Models, https://github.com/dpkingma/nips14-ssl * RNN, agents, “bricks”: https://github.com/bartvm/blocks * NTM, https://github.com/shawntan/neural-turing-machines/ * RL + CNN, https://github.com/brian473/neural_rl * DRAW RNN, https://github.com/jbornschein/draw And this is far from complete, there are countless more examples. Just search on GitHub. I just filtered out the ones which interest me (which at least have RNNs/LSTMs or some other interesting things).
In Keras: Theano-Based Deep Learning Library

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