90. What are the challenges in Reinforcement Learning?

Major Challenges

1. Large Training Time 
RL models may require millions of interactions.

2. Sparse Rewards 
Rewards may occur rarely, making learning difficult.

3. Exploration Problems 
Agent may not explore enough useful actions.

4. High Computational Cost 
Training RL systems requires powerful hardware.

5. Stability Issues 
Training can become unstable in complex environments.

👉 Example: Training autonomous driving AI safely in real-world environments is extremely challenging.

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