[RLlib] Is IMPALA applicable to continuous action spaces?
Nobody has claimed this yet.
Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 62/100
- Issue type
- Documentation
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- documentation, machine-learning
Research direction
Read the RLlib algorithm documentation at docs.ray.io/en/latest/rllib/rllib-algorithms.html and inspect rllib/algorithms/impala/impala.py. Compare the documented action-space support with the implementation, then update the relevant documentation to accurately state whether IMPALA supports continuous action spaces.
Written by the indexing model from the issue text.
Description
Description
According to the source code and practical applications, it seems to be. Why is it not stated in the documentation that it is applicable to continuous action spaces?
Link
https://docs.ray.io/en/latest/rllib/rllib-algorithms.html
https://github.com/ray-project/ray/blob/master/rllib/algorithms/impala/impala.py
- Dominant language
- Python
- Stars
- 43.9k
- Forks
- 8.1k
- Avg merge
- 4d 15h
- Merged PRs (30d)
- 245
Contributor guide
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