AI agents are diverse, ranging in complexity based on their capabilities and how they process information to make decisions. One fundamental type is the simple reflex agent, which acts solely based on the current percept without considering past experiences. Building upon this, model-based reflex agents maintain an internal state of the environment to handle partially observable situations. More sophisticated agents include goal-based agents, which utilize future goals to select actions that lead towards desired outcomes. Even further advanced are utility-based agents, designed to maximize their expected utility by weighing different goals and their likelihood of success. Finally, learning agents represent an adaptive category, capable of improving their performance over time through experience and feedback, encompassing many modern AI systems. More details: https://info-news.top