rl-evaluation
CommunityRigorous RL evaluation for statistical validity.
Education & Research#statistics#generalization#research-methods#confidence-intervals#experimental-design#rl-evaluation#multiseed
Authortachyon-beep
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill provides a structured approach to evaluating RL agents with statistical rigor, ensuring results are reliable, reproducible, and suitable for publication or deployment.
Core Features & Use Cases
- Multi-seed evaluation protocol with mean, std, and confidence intervals to quantify performance.
- Generalization and distribution-shift testing to assess robustness beyond the training environment.
- Clear reporting templates for papers and dashboards, including sample-efficiency and significance tests.
Quick Start
Use the rl-evaluation skill to set up a multi-seed evaluation for your agent, run 5-20 seeds, and generate a results summary.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: rl-evaluation Download link: https://github.com/tachyon-beep/hamlet/archive/main.zip#rl-evaluation Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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