Reinforcement Learning

Imagine teaching a dog a trick. You reward it for good behavior and gently correct mistakes. This is similar to how machines learn in reinforcement learning, a fascinating branch of AI where agents learn through trial and error.

Learning on the Job: What is Reinforcement Learning?

Unlike supervised learning, where machines are fed labeled data, reinforcement learning agents interact with an environment and learn from their experiences. Think of it as playing a video game – you learn by trying different actions and seeing what works best. In reinforcement learning, the agent receives rewards for successful actions and penalties for mistakes. Over time, the agent learns to navigate the environment and maximize its rewards.