DDPG documnetation tweaks; added Q loss equations and light explanation

[dosssman]

Description

• Fixed a few typos and proposed some reformulations of a few sentences.
• Added a little bit more details regarding DDPG's Q loss.

Other comments

• Regarding the hard time reproducing ddpg on Mujoco-v1, I was wondering how feasible it would be to run fujimoto's DDPG.py etc.. on free-mujoco

Other than that, great job on the pretty complete documentation for DDPG @vwxyzjn @yooceii , and sorry for being late to the party 🙇

Types of changes

• Bug fix
• New feature
• New algorithm
• Documentation

Checklist:

• I've read the CONTRIBUTION guide (required).
• I have ensured pre-commit run --all-files passes (required).
• I have updated the documentation and previewed the changes via mkdocs serve.
• I have updated the tests accordingly (if applicable).

If you are adding new algorithms or your change could result in performance difference, you may need to (re-)run tracked experiments. See #137 as an example PR.

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• I have tracked applicable experiments in openrlbenchmark/cleanrl with --capture-video flag toggled on (required).
• I have added additional documentation and previewed the changes via mkdocs serve.
  • I have explained note-worthy implementation details.
  • I have explained the logged metrics.
  • I have added links to the original paper and related papers (if applicable).
  • I have added links to the PR related to the algorithm.
  • I have created a table comparing my results against those from reputable sources (i.e., the original paper or other reference implementation).
  • I have added the learning curves (in PNG format with width=500 and height=300).
  • I have added links to the tracked experiments.
• I have updated the tests accordingly (if applicable).

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[gitpod-io]

[vwxyzjn]

This PR is a follow-up on #137. Thanks @dosssman for this fix! I will take a look at it tomorrow :)

Regarding the hard time reproducing ddpg on Mujoco-v1, I was wondering how feasible it would be to run fujimoto's DDPG.py etc.. on free-mujoco

There it is: https://wandb.ai/openrlbenchmark/openrlbenchmark/reports/MuJoCo-sfujim-TD3--VmlldzoxNzIyODIz

[dosssman]

Thanks. The report seems privated though:

[vwxyzjn]

Could you try it again?

[dosssman]

All good now

[vwxyzjn]

LGTM. Thanks!