Comments (1)
Yes, it's because of action repeat. The slight increase is just to make sure the agent not just reaches the budget but also write logs afterwards. For reporting results, of course we cut off any steps beyond the budget.
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Related Issues (20)
- Need some clarifications about details in Atari env HOT 1
- How are online trajectories sampled? HOT 1
- How to add dropout HOT 1
- [Question] Adding separate optimizers/loss functions per network HOT 2
- Invalid syntax `segment = prob[*path]` HOT 2
- Clarification on `carry` variable used during training
- AttributeError: type object 'Module' has no attribute '__annotations__' HOT 1
- Slow operation for convolution HOT 5
- Question about integration of Plan2Explore HOT 1
- Outdated README for custom environment and mlp_keys/cnn_keys HOT 2
- Replay parameters
- Where is the actual evaluation reward?
- The 12M model sizes doesn't align with the paper
- Package structure
- Why is the posterior being sampled for the policy during inference?
- Latest update of ale-py breaks the Dockerfile instructions
- Evaluation
- ale-py 0.9.0 No module named 'ale_py.roms.utils'
- Pong results do not match paper HOT 1
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