How do I evaluate reinforcement learning models?

How do I evaluate reinforcement learning models?

Evaluating reinforcement learning models involves assessing their performance using metrics like cumulative reward, convergence, and stability.

What metrics should I focus on for evaluation?

Key metrics include average reward, success rate, and learning curve. These help gauge how well the model is learning.

Can you explain how to calculate the average reward?

The average reward is calculated by taking the total reward received over a number of episodes and dividing it by the number of episodes.

What tools can I use for this evaluation?

You can use libraries like OpenAI Gym for environments, and TensorFlow or PyTorch for model training and evaluation.