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Hello,
Is there any benefit to having a vanilla REINFORCE algorithm for people trying to learn the concepts? REINFORCE with Baseline includes a value function approximator which has a lot of simila…
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I'm running several nested bars. The inner bars may be run many times for each step of the outer bars. When an inner bar completes, it "stays around", and a new version of the bar pops up underneath.
…
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在您的 policy_gradient.py 文件中,请问 self.mu 需要乘多少是如何确定的呢?
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# Reference
- 07/2017 [Proximal policy optimization algorithms](https://arxiv.org/abs/1707.06347)
# Brief
- 基于策略梯度(PG,Policy Gradient)
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[Policy Gradient Methods for Reinforcement Learning with Function Approximation](https://papers.nips.cc/paper/1713-policy-gradient-methods-for-reinforcement-learning-with-function-approximation.pdf)
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### System Info
- `transformers` version: 4.44.0
- Platform: Linux-5.4.0-162-generic-x86_64-with-glibc2.31
- Python version: 3.11.9
- Huggingface_hub version: 0.23.4
- Safetensors version: 0.4.…
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hi, thank you for your brilliant work, i have got many from your work.
I'm ready to do related research, but i can't find the code of NeurIPS 2022 paper "The Policy-gradient Placement and Generativ…
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I am confused by your code.
In the paper, it is mentioned that a policy gradient method [1] is used. But more specifically, I think that is implemented by Actor-Critic.
If I am wrong, plz tell m…
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## Problem Description
_This is more a question than a problem_
In the ppo implementation, why advantage normalization is done for pg_loss, not for vf_loss? Say we have a rl env with a dense reward …
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Hi.
The code [Code](https://github.com/adventuresinML/adventures-in-ml-code/blob/master/policy_gradient_reinforce_tf2.py ) is not working with this line: `loss = network.train_on_batch(states, discou…