DeepRL-Agents
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awjuliani
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Hi, your repo is very helpful for me to learn RL in action. In `A3C-Doom.ipynb`, I found the code spawns multi-threads to train the model, in Python threading cannot make...
A3C is multithread code and does it need a lock while excuting function apply_gradients?
(Ref. line 97 in gridworld.py) Shouldn't the 'done' flag be TRUE when the 'hero' reaches either 'goal' or 'fire'? Currently checkGoal( ) always returns a FALSE 'done' status.
I switched machines, tried this in python 2 and 3. DIdn't see this before. directory contains all 3 files but it simply won't load the other two modules. Any idea...
Running the Double-Dueling-DQN code results in a network, that stops learning after about 2000 episodes., i.e. the game results do not get better. Run the GridWorld example now four different...
I've encountered the thing that I can't understand while following up the Double-Dueling-DQN.ipynb. There's a def like below ``` def updateTargetGraph(tfVars,tau): total_vars = len(tfVars) op_holder = [] for idx, var...
Did anyone managed to get the A3C LSTM of this repo to work for Pong (using the openai gym)? I have already tried several different optimizers, learning rates, network architectures,...
File: https://github.com/awjuliani/DeepRL-Agents/blob/master/A3C-Doom.ipynb Where: A typo in a comment of the final gist What: "# Start the "work" process for each worker in a separate threat." Correction: threat => thread
I run the code and meet a problem like this: ********************************************************* Target Set Success 5000 0.65 1 98%|█████████████████████████████████████████▏| 50/51 [00:00
