Deep Q-Learning Network in pytorch (not actively maintained)

Related tags

Deep Learning deep-reinforcement-learning pytorch deep-q-network
Overview

pytoch-dqn

This project is pytorch implementation of Human-level control through deep reinforcement learning and I also plan to implement the following ones:

Credit

This project reuses most of the code in https://github.com/berkeleydeeprlcourse/homework/tree/master/hw3

Requirements

  • python 3.5
  • gym (built from source)
  • pytorch (built from source)

Usage

To train a model:

$ python main.py

# To train the model using ram not raw images, helpful for testing

$ python ram.py

The model is defined in dqn_model.py

The algorithm is defined in dqn_learn.py

The running script and hyper-parameters are defined in main.py

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Comments
  • Take a long time to converge

    Take a long time to converge

    I run the code,and found your dqn algorithm take such a long time to converge.Actually,I found few implementation of dqn can converge in github.They can converge in a afternoon.I use a piece of GTX1080Ti.It is appreciate that your implementation can converge.But your code take a day and a night to converge.I don't know why.

    opened by Ja1r0 1
  • ImportError: No module named 'openai_benchmark'

    ImportError: No module named 'openai_benchmark'

    ubuntu 16.04 python3.5 anaconda installed gym refered https://github.com/openai/gym instruction. but when i run your code

    Traceback (most recent call last): File "/home/op/pytorch-dqn-master/main.py", line 3, in import openai_benchmark ImportError: No module named 'openai_benchmark'

    i found in the search engine, someone runs dir(gym),the result contains 'benchmark_spec', 'benchmarks', but none on my pc.

    opened by jixian79 4
  • Fixes for issues #3, #5 and #7. Agent learns better

    Fixes for issues #3, #5 and #7. Agent learns better

    Below is the summary of the contributions made by this PR:

    • [x] Fixes for issues #3, #5 and #7
    • [x] Overcomes the limitation of #4. This PR enables the agent to collect more rewards with minimal changes to the original scripts.
    • [x] Tested with Pytorch 0.2 (as requested in #5 )
    opened by praveen-palanisamy 2
  • pytorch 0.2

    pytorch 0.2

    I'm running pytorch 0.2,

    and the code dqn_learn.py fail to work..

    the error as follow

    Traceback (most recent call last):
  File "ram.py", line 57, in <module>
    main(env)
  File "ram.py", line 46, in main
    target_update_freq=TARGER_UPDATE_FREQ,
  File "/auto/master05/ssarcandy/ttt/dqn_learn.py", line 213, in dqn_learing
    current_Q_values.backward(d_error.data.unsqueeze(1))
  File "/home/master/05/ssarcandy/.local/lib/python2.7/site-packages/torch/autograd/variable.py", line 156, in backward
    torch.autograd.backward(self, gradient, retain_graph, create_graph, retain_variables)
  File "/home/master/05/ssarcandy/.local/lib/python2.7/site-packages/torch/autograd/__init__.py", line 98, in backward
    variables, grad_variables, retain_graph)
  File "/home/master/05/ssarcandy/.local/lib/python2.7/site-packages/torch/autograd/function.py", line 91, in apply
    return self._forward_cls.backward(self, *args)
  File "/home/master/05/ssarcandy/.local/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py", line 566, in backward
    return grad_input.scatter_add_(ctx.dim, index, grad_output), None, None
  File "/home/master/05/ssarcandy/.local/lib/python2.7/site-packages/torch/autograd/variable.py", line 696, in scatter_add_
    return ScatterAdd.apply(self, dim, index, source, True)
  File "/home/master/05/ssarcandy/.local/lib/python2.7/site-packages/torch/autograd/_functions/tensor.py", line 605, in forward
    return input.scatter_add_(ctx.dim, index, source)
RuntimeError: invalid argument 3: Index tensor must have same dimensions as input tensor at /pytorch/torch/lib/THC/generic/THCTensorScatterGather.cu:198
    opened by SSARCandy 2
Owner
Hung-Tu Chen
Graduate Student at Dartmouth PBS
Hung-Tu Chen
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