-
Hey, thanks for providing purejaxrl is pretty awesome.
I have used the experimental `S5` code that you provide for a part of my research and after version 0.4.27 (same for 0.4.28) of `jaxlib` I hav…
-
https://datawhalechina.github.io/easy-rl/#/chapter1/chapter1
Description
-
## Describe the bug
When the batched env device is `cuda` the step count on the batched env seems completely off from what it should be.
When the batches env device is `mps` there is a segmentatio…
-
Hi Mr Klein,
I am a master student in data science from Lancaster University and I am trying to understand the SCIRL and CSI algorithms mentioned in your paper. I tried to run the Exp7.ipynb from i…
-
Hello, the algo doesn't work for continuous_mountain_car, because it's reward is -pow(action[0],2)*0.1. What means, the car's initial state is a local max reward, all the exploration will decrease the…
-
## Describe the bug
Not quite sure if this is supported behavior, but if I set `functional=True` for the A2C loss and `shifted=True` for `TD0Estimator` I get an internal error.
## To Reproduce
…
-
Hello,
I've tried in vain to find suitable hyperparameters for SAC in order to solve MountainCarContinuous-v0.
Even with hyperparameter tuning (see "add-trpo" branch of [rl baselines zoo](https:…
-
When trying to debug the following piece of code,
`using OpenAIGym`
`env = GymEnv("MountainCar-v0") # offending line`
the debugger crashes all the time. I have tried it both in Linux(Ubuntu) an…
-
**What version of AgileRL are you using?**
1.0.0
**What operating system and processor architecture are you using?**
Windows 11 x64
**What did you do?**
Steps to reproduce the behaviour:
…
sryu1 updated
2 months ago
-
Hey,
I was trying to build the MountainCar-v0 Env but while training I noticed the random steps taken which was in my input data were not efficient and didn't work well, So I decided to give it inp…