How can I tune reinforcement learning algorithms for my C++ game?

How can I tune reinforcement learning algorithms for my C++ game?

Tuning reinforcement learning algorithms involves adjusting hyperparameters like learning rate, discount factor, and exploration strategies. What specific algorithm are you using?

I'm using Deep Q-Learning. What parameters should I focus on?

For Deep Q-Learning, focus on the learning rate, batch size, and the epsilon decay for exploration. Have you set up experience replay?

Yes, I have experience replay implemented. How can I optimize it?

You can optimize experience replay by adjusting the replay buffer size and sampling strategies. Consider prioritizing experiences based on their TD error.

That sounds helpful! Any tips on monitoring the training process?

Monitor the average reward and loss over episodes. Visualizing these metrics can help you identify if your model is converging.