DeepRL-Agents
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awjuliani
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Hi ! Thanks for your articles about RL I really enjoyed them. In the notebook about Q-Table, I've made some modifications: - I've added some explanations (Q algo pseudocode), comments...
I ran the notebook without any changes on the vizdoom environment. After around an hour the reward became non-negative and peaked at around 0.7, but continuing to run the code...
Hi I would like to share with you the effect of gamma on performance - I believe that when **gamma = 0.99** means that we think that next future states...
see `dqn.zip` below 1. corrected code from `Deep-Recurrent-Q-Network.ipynb` `zip` now is a class, so need to convert to `list`: `episodeBuffer = list(zip(bufferArray))` 1. corrected `helper.py` [dqn.zip](https://github.com/awjuliani/DeepRL-Agents/files/949664/dqn.zip)
hi Based on [ViZDoom](http://www.cs.put.poznan.pl/wjaskowski/pub/papers/Kempka2016ViZDoom.pdf) paper figure 7, I tried to use skip count to speed up the training, as follows: `r = self.env.make_action(self.actions[a], 4) / 100.0` However, the agent performed...
Hi, Sorry for stupid question I've done training process. Now I'm looking for execute the agent to play the Doom game but didn't see that piece of code. Could you...
Wondering if anyone's had success implementing a _deep_ RNN in [AC_Network()](https://github.com/awjuliani/DeepRL-Agents/blob/master/A3C-Doom.ipynb)? At first glance it looks as easy as ``` cell = tf.nn.rnn_cell.LSTMCell(256, state_is_tuple=True) cell = tf.nn.rnn_cell.MultiRNNCell([cell] * 2, state_is_tuple=True)...
Episodes are not terminated when _episode_step_count_ exceeds _max_episode_length_. It is not necessarily a problem, but as both summary writing and model saving is dependent on episode_count, if the episodes are...
IOError: [Errno 2] No such file or directory: './Center/log.csv' Any ideas my friend? Trying to run Deep-Recurrent-Q-Network.ipynb File "D-R-Q.py", line 153, in with open('./Center/log.csv', 'w') as myfile: IOError: [Errno 2]...
