Comments (3)
I got Pong working after 1.0, but yes I recently observed this drop in Space Invaders. I don't think the epsilon greedy value is the problem (I think that was needed for getting correct scores on Pong, because with too much noise the agent would miss the ball and lose points). The other changes between 1.0 and master are a) adding gradient clipping b) using the prioritised loss for the prioritised weights. I'm going to try Space Invaders and disable gradient clipping, so if you're able to revert b) and run with default settings (no QR) then that would help find the problem.
from rainbow.
Hum... I did a sanity check with your release v1.0 this week-end (commit 952fcb4).
The performance I got are really different from the one you are showing.
I opened a new issue there #26
from rainbow.
Closing this as I don't know what performance changing to QR in Rainbow should cause, but leaving the other issue open until the issue there is resolved.
from rainbow.
Related Issues (20)
- Infinite loop in ReplayMemory._get_sample_from_segment HOT 1
- Noob Question : Need help running the code. It seems to be running for forever. HOT 1
- rainbow for multiagent setting HOT 1
- Policy and reward function HOT 4
- ploting the result HOT 1
- To run a demo HOT 2
- disable env.reset() after every episode HOT 5
- --learn-start HOT 2
- Delayed reward HOT 1
- load a model HOT 1
- Explanation of Q statistics in plots for "val_mem"? HOT 1
- [question] Training speed HOT 3
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- IndexError: index 262141 is out of bounds for axis 0 with size 231071 HOT 2
- Evaluate the pretrained model HOT 1
- The problem about training with GPU HOT 1
- Stuck in memory._retrieve when batch size > 32 HOT 1
- A problem about one game in ALE cannot be trained HOT 1
- Montezuma's revenge - has this been tried using this codebase? HOT 2
- Data Effiecient Rainbow with Skiing does not work HOT 4
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from rainbow.