What is the Actor-Critic model in reinforcement learning?

What is the Actor-Critic model in reinforcement learning?

The Actor-Critic model is a type of reinforcement learning algorithm that combines two components: the actor, which decides on actions, and the critic, which evaluates the actions taken.

How does the actor learn to make better decisions?

The actor learns by receiving feedback from the critic, which assesses the quality of the actions taken based on the rewards received.

What are the advantages of using the Actor-Critic model?

Some advantages include improved stability and efficiency in learning, as it balances exploration and exploitation effectively.

Can you give an example of where this model is used?

Sure! The Actor-Critic model is often used in complex environments like robotics and game playing, where decision-making is crucial.