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Hello, I'm trying to train a policy for VMAS simple spread environment using MAPPO and IPPO in Benchmarl.
However, I'm suffering with some issues while training and it would be great if I can get an…
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# Pierre-Luc Bacon
The project description suggests that RLPy is mainly about value function based algorithms. However, I think it'd be nice to add Will Dabney's implementation of some of the popular…
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WARNING: Logging before InitGoogleLogging() is written to STDERR
I1022 16:02:46.179663 104725 init.cc:47] Init commandline: dummy run.py --tryfromenv=use_pinned_memory,check_nan_inf,benchmark,warpctc…
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https://scholar.google.com/scholar?hl=ja&as_sdt=0%2C5&q=Deterministic+Policy+Gradient+Algorithms&btnG=
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http://proceedings.mlr.press/v32/silver14.pdf
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Thank you for your great work!
I refactored the code [repo is here](https://github.com/baichen99/Finite-expression-method/blob/main/train_fex_possion.py), but it seems that the use of policy gradie…
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- refering to [this part](https://github.com/openai/spinningup/blob/master/spinup/algos/pytorch/vpg/vpg.py#L240) from VPG
```py
# Get loss and info values before update
pi_l_old…
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When I try to use a 4-gpus machine to run the Analytic policy gradients training in parallel, it reports an AssertionError in `brax/training/agents/apg/train.py` line 255. Seems that it is because `t…
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Hi @yanji84,
first of all compliments on your code, the clear structure makes it easy to understand. However, I think there are two issues with how you compute the policy gradients in the `backward…
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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…