Reinforcement Learning (RL) is a type of AI training where an agent learns to make decisions by interacting with its environment. The agent receives rewards for good actions and penalties for bad ones, helping it learn the best strategies over time.
RL is used to train AI to play games like chess or Go, where the system learns strategies by playing repeatedly and adjusting based on wins or losses.
Reinforcement learning is ideal for tasks where trial-and-error and long-term planning are important.