Using Deep RL Meta-Skill

When to Use This Skill

Invoke this meta-skill when you encounter:

• RL Implementation: Implementing reinforcement learning algorithms (Q-learning, DQN, PPO, SAC, etc.)
• Agent Training: Training agents in environments (games, robotics, control systems)
• Sequential Decision-Making: Problems requiring learning from trial and error
• Policy Optimization: Learning policies that maximize cumulative rewards
• RL Debugging: Debugging training issues, agents not learning, reward problems

This is the entry point for the deep-rl pack. It routes to 13 specialized skills based on problem characteristics.

How to Access Reference Sheets

IMPORTANT: All reference sheets are located in the SAME DIRECTORY as this SKILL.md file.