AI agents can be classified into several types based on their capabilities and functionalities. Reactive agents respond to their environment without retaining memory or learning from past experiences, executing actions based on predefined rules or current inputs. Deliberative agents, on the other hand, use reasoning and decision-making processes to plan and execute actions, often incorporating learning from past actions. Hybrid agents combine both reactive and deliberative approaches, adapting their behavior depending on the context and task complexity. Moreover, learning agents improve their performance through interaction with the environment, utilizing algorithms like reinforcement learning to adjust their strategies. Finally, autonomous agents operate with a high degree of independence, making decisions and executing tasks without direct human intervention.