pg_rnn
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abhishm
There are few caveats when you want to use a Recurrent Neural Network (RNN) policy with Policy Gradient Algorithms. This repository explains them and provide a solution for them. Please see the blog f...
Hi. When I run your code, I find a mistake in run_pg_rnn.py. The last line print("reward is {0}".format(np.sum(episode["rewards"]))) should be print("reward is {0}".format(np.sum(episode["returns"]))) Besides, why is the reward always 0?
Hello, I want to involve RL into my RNN model, your code is a great beginning to me. I have a question about the gradient calculation part in your '/pg_rnn.py'...
