Questions tagged [a3c]
For questions related to the asynchronous advantage actor-critic (A3C) algorithm.
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Understanding loss function gradient in asynchronous advantage actor-critic (A3C) algorithm
This is a question I posted here. I am asking it on this StackExchange branch as well, so that more people who could potentially answer get to see the question.
In the A3C algorithm from the original ...
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1answer
105 views
How do I create a custom gym environment based on an image?
I am trying to create my own gym environment for the A3C algorithm (one implementation is here). The custom environment is a simple login form for any site. I want to create an environment from an ...
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Why would the reward of A3C with LSTM suddenly drop off after many episodes?
I am training an A3C with stacked LSTM.
During initial training, my model was giving descent +ve reward. However, after many episodes, its reward just goes to zero and is continuing for a long time. ...
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Does normal A3C works well for continuous state space?
I am trying to create an A3C but it is giving same action for all the states during the training.
The same action is also not an obvious way to maximise the reward.
However I donot know if normal a3c ...
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is it ok to take random actions while training a3c as in below code
i am trying to train an A3C algorithm but I am getting same output in the multinomial function.
can I train the A3C with random actions as in below code.
can someone expert comment.
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When past states contain useful information, does A3C perform better than TD3, given that TD3 does not use an LSTM?
I am trying to build an AI that needs to have some information about the past states as well. Therefore, LSTMs are suitable for this.
Now, I want to know that for a problem/game like Breakout, where ...
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1answer
244 views
Why do we also need to normalize the action's values on continuous action spaces?
I was reading here tips & tricks for training in DRL and I noticed the following:
always normalize your observation space when you can, i.e., when you know the boundaries
normalize your ...
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1answer
160 views
How does being on-policy prevent us from using the replay buffer with the policy gradients?
One of the approaches to improving the stability of the Policy
Gradient family of methods is to use multiple environments in
parallel. The reason behind this is the fundamental problem we
discussed in ...
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How should I deal with variable batch size in A3C?
I am fairly new to reinforcement learning (RL) and deep RL. I have been trying to create my first agent (using A3C) that selects an optimal path with the reward being some associated completion time (...
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1answer
62 views
What is the pros and cons of increasing and decreasing the number of worker processes in A3C?
In A3C, there are several child processes and one master process. The child precesses calculate the loss and backpropagation, and the master process sums them up and updates the parameters, if I ...
