AI Agent

Last Updated: July 29, 2026 | By Mihail Sebastian | AI Dictionary

A system that perceives its environment, decides what to do, and acts to reach a goal – from simple rule-based programs to systems that learn and adapt.

What is an AI Agent?

An AI agent is a system that runs a loop: it perceives its environment, decides what to do, and acts – then perceives the result and goes again. Agents range from simple rule-followers to systems that learn and adapt with experience.

The term names the system itself; the broader design approach of building AI that pursues goals autonomously is called agentic AI.

Types of AI Agents

  1. Reactive agents respond directly to what they sense, with no memory of the past: the same input always produces the same response.
  2. Deliberative agents keep an internal model of their environment and plan ahead, weighing future consequences before acting.
  3. Learning agents improve with experience, adjusting their behavior based on what worked and what didn’t.

Applications of AI Agents

Example of an AI Agent

A robotic vacuum cleaner is the perceive-decide-act loop in miniature. Its sensors detect walls, furniture, and drop-offs (perception); it picks a cleaning path and reroutes around obstacles (decision); and it drives that path (action), then senses the new position and repeats.

No one steers it: given the goal of a clean floor, it works out the rest.

Related AI terms: Agentic AI · Reinforcement Learning · Chatbot · Robotic Process Automation · ROS

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Mihail Sebastian — Writes about AI governance, regulation, and the technology behind them. Placeholder bio — replace with a real credential line. About

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