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In the results of Chapter 14 Deterministic policy gradients in the book,
why the training is not very stable and noisy?
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![擷取](https://user-images.githubusercontent.com/475557…
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here is the solution
https://github.com/philtabor/Multi-Agent-Deep-Deterministic-Policy-Gradients/issues/2#issuecomment-912548033
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[Distributed Distributional Deterministic Policy Gradients](D4PG)
Reference implementation:
- https://github.com/deepmind/acme
PyTorch implementation:
- https://github.com/fabiopardo/tonic
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The pricing policy has parameters $\theta$s, and our goal is to optimized the simulation in order to produce max profits.
To do so, we need to calculate gradient of objective function(profit) w.r…
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https://github.com/philtabor/Multi-Agent-Deep-Deterministic-Policy-Gradients/blob/a3c294aa6834f348a7401306dff3e67919c861f5/maddpg.py#L74
Hi Phill,
Could you please help me to understand what's …
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Hi, Thank you for sharing the repo!
I was wondering how the Train_Return and Test_Return is calculated
and what the difference between the two.
I see that one is using norm_a_tf and sample_a_tf …
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Hi, may I ask which paper code is this?
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### 🐛 Describe the bug
I was wondering anyone having experiences with full parameter fine tuning of Llama 2 7B model using FSDP can help: I put in all kinds of seeding possible to make training deter…