Learn the main types of AI agents, how they work, and when to use each model, from simple reflex agents to learning and goal-based agents.

databricks

AI agents are evolving from simple automation to systems that observe, decide, and act across real workflows. This guide presents a stable framework for understanding five core agent types based on decision behavior: simple reflex agents (condition-action rules), model-based reflex agents (maintain internal state), goal-based agents (plan toward outcomes), utility-based agents (optimize trade-offs), and learning agents (adapt from feedback). The framework helps teams choose appropriate agent designs by matching problem characteristics with agent capabilities, avoiding overengineering, and balancing trade-offs between predictability, adaptability, and operational complexity. Most production agents are hybrids combining multiple approaches for reliability and responsiveness.

Types of AI Agents: Definitions, Roles, and Examples