Types of AI Agents: Definitions, Roles, and Examples
🤖 AI agents are evolving to execute real actions, moving beyond simple predictions. These agents adapt using reflex, model-based, goal-based, utility-based, and learning approaches, balancing predictability and adaptability. The choice of agent depends on task complexity; simple tasks need basic agents, while dynamic tasks require planning. Successful AI agents combine reflexes, planning, and learning, with gradual scaling. As AI stakes rise, they demand early consideration of autonomy, control, and governance to prevent cascading errors in workflows.
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