reinforcement-learning
byaznatkoiny· 9 skills
Reinforcement Learning best practices for Python using modern libraries (Stable-Baselines3, RLlib, Gymnasium). Use when: - Implementing RL algorithms (PPO, SAC, DQN, TD3, A2C) - Creating custom Gymnasium environments - Training, debugging, or evaluating RL agents - Setting up hyperparameter tuning for RL - Deploying RL models to production
How to install reinforcement-learning?
aznatkoiny/zai-skills/reinforcement-learning
$npx -y skills add aznatkoiny/zai-skills --skill reinforcement-learningInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/aznatkoiny/zai-skills" --skill "aznatkoiny/zai-skills/reinforcement-learning"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/aznatkoiny/zai-skills" that are relevant to the current task. Run `npx skills add "https://github.com/aznatkoiny/zai-skills"` and select the relevant skills, then follow their instructions.
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