What are the key algorithms in reinforcement learning?

What are the key algorithms in reinforcement learning?

The key algorithms in reinforcement learning include Q-learning, Deep Q-Networks (DQN), Policy Gradients, and Actor-Critic methods.

Can you explain how Q-learning works?

Q-learning is a model-free algorithm that learns the value of actions in states to maximize cumulative rewards.

What is the difference between Q-learning and Policy Gradients?

Q-learning focuses on learning action values, while Policy Gradients directly optimize the policy for better action selection.

Are there any real-world applications of these algorithms?

Yes, they are used in robotics, game playing, and autonomous systems, among other fields.