Reinforcement Learning

Reinforcement learning is a method in which an agent (AI) learns to maximize reward through interaction with its environment. Through repeated trial and error, the agent autonomously learns "what action to take in a given situation to gain the most reward." Unlike supervised learning, where correct labels are provided, reinforcement learning works by returning a "reward" or "penalty" in response to a given action. The agent learns a policy (action strategy) that maximizes these rewards. Fundamental components of reinforcement learning: • Agent: The learning entity that selects actions • Environment: The world the agent operates in (e.g., a game, simulation space) • State: The current condition of the environment • Action: The choices available to the agent • Reward: The evaluation received as a result of an action • Policy: The strategy that defines how actions are chosen • Value function: A numerical estimate of how promising a given state or state-action pair is Representative fields where reinforcement learning is used: • Game AI: Advanced strategy AI such as AlphaGo and OpenAI Five • Robotics: Autonomous navigation, object manipulation, drone control • Autonomous driving: Optimizing driving decisions in context • Ad delivery and recommendation: Long-term optimization accounting for user behavior Representative algorithms: • Q-Learning • SARSA • DQN (Deep Q-Network) • PPO (Proximal Policy Optimization) • A3C (Asynchronous Advantage Actor-Critic) A key strength of reinforcement learning is the ability to make decisions that consider long-term outcomes. On the other hand, it requires extensive trial-and-error and high computational cost. In recent years, "deep reinforcement learning," which combines deep learning and reinforcement learning, has emerged, enabling highly accurate action selection even in complex environments. Reinforcement learning is the archetypal framework for "AI that learns on its own" and is an indispensable technology for realizing more advanced, flexible artificial intelligence.