Individual skill
spinning-up-deep-rl
Learn or apply deep reinforcement learning with OpenAI Spinning Up: policy gradients, VPG, PPO, SAC, TD3, DDPG, TRPO. Use whenever an RL agent will not learn, reward stays flat, or the user asks how PPO or SAC works.
engineering/spinning-up-deep-rl/skills/spinning-up-deep-rl/SKILL.md
Source commit 8f082544116fc0d014188e521ca40304cdfc86b0
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 10, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 29,589
- Repository last updated
- Nov 5, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agentic-ai Repository topic
- anthropic-claude Repository topic
- claude-ai Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- claude-code-skills Repository topic
- ai-coding-agent Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- openai-codex Repository topic
- education Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 11,043 bytesSKILL.mdcore · 11,043 byteschapters/ch01-introduction.mddoc · 6,145 byteschapters/ch02-installation.mddoc · 3,875 byteschapters/ch03-algorithm-lineup.mddoc · 5,795 byteschapters/ch04-running-experiments.mddoc · 6,184 byteschapters/ch05-experiment-outputs.mddoc · 4,588 byteschapters/ch06-plotting-results.mddoc · 3,928 byteschapters/ch07-key-concepts-in-rl.mddoc · 8,029 byteschapters/ch08-kinds-of-rl-algorithms.mddoc · 8,219 byteschapters/ch09-intro-to-policy-optimization.mddoc · 8,712 byteschapters/ch10-spinning-up-as-a-researcher.mddoc · 10,392 byteschapters/ch11-key-papers-in-deep-rl.mddoc · 4,608 byteschapters/ch12-exercises.mddoc · 5,528 byteschapters/ch13-benchmarks.mddoc · 4,986 byteschapters/ch14-vpg.mddoc · 4,968 byteschapters/ch15-trpo.mddoc · 6,053 byteschapters/ch16-ppo.mddoc · 7,002 byteschapters/ch17-ddpg.mddoc · 7,541 byteschapters/ch18-td3.mddoc · 6,037 byteschapters/ch19-sac.mddoc · 7,852 byteschapters/ch20-logger-and-utilities.mddoc · 4,807 bytescheatsheet.mddoc · 5,010 bytesglossary.mddoc · 5,446 bytespatterns.mddoc · 7,927 bytes
Read excerpt
# Spinning Up in Deep RL
**Author**: Joshua Achiam (OpenAI) | **Source**: spinningup.readthedocs.io, MIT | **Chapters**: 20 | **Generated**: 2026-08-25
## How to Use This Skill
- **No argument** — load the core frameworks below
- **A topic** — ask about `advantage function`, `target networks`, `entropy regularization`;
I resolve it through the Topic Index and read that chapter file
- **`chNN`** — I load that chapter's summary
- **"what chapters do you have?"** — the full index
```
/cs-spinning-up-deep-rl # core frameworks + chapter index