Key Concepts Agents Environments Rewards And States

# Key Concepts: Agents, Environments, Rewards, and States in Reinforcement Learning Imagine teaching a dog a new trick. You show them what to do, reward them when they get it right, and correct them when they don't. This, in essence, is what reinforcement learning (RL) is all about. But instead of dogs, we have "agents," and instead of real-world scenarios, we have "environments." Reinforcement learning is a powerful paradigm for training intelligent agents to make decisions in complex environ