Reinforcement Learning Best Practices

Overview

This skill provides comprehensive guidance for implementing reinforcement learning in Python using the modern ecosystem (2024-2025). Gymnasium has replaced OpenAI Gym as the standard environment interface. Stable-Baselines3 (SB3) is recommended for prototyping, RLlib for production/distributed training, and CleanRL for research.

When to Use

• Building RL agents for discrete or continuous control tasks
• Creating custom simulation environments
• Tuning hyperparameters for RL algorithms
• Debugging training issues (reward curves, policy collapse, numerical instability)
• Deploying trained policies to production

Library Selection