Comments (4)
Sorry, I didn't fully run the atari experiment, since I don't have enough resource to run it 😟 (by calculation, it needs roughly 1T RAM and weeks of training on my environment).
If you have enough resource and want to replicate the results, I suggest you to try the parameters in Appendix A of the paper. My setting is --expl epsilon_greedy --horizon 10 --kl_scale 0.1 --action_dist onehot --expl_amount 0.4 --expl_min 0.1 --expl_decay 100000 --pcont 1 --time_limit 1000000
. Here time_limit
is set to be large enough to prevent early stop of rollout in atari environment.
You may also need to change the hidden size of the network as mentioned by Danijar in #7.
Good Luck!
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DreamerV2 for Atari games is out. Check this repo: https://github.com/danijar/dreamerv2
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Same problem as #29.
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Ty! Does Atari learn well (replicate results) with the hyperparameters in dreamer.py?
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Related Issues (20)
- A question about reward and observation pairing in wrapper HOT 2
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