What are the main types of AI agents?

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AI agents are entities that perceive their environment through sensors and act upon it using actuators to achieve specific goals. The main types of AI agents are:

1. Simple Reflex Agents – Act only on the current percept, ignoring history. They use condition–action rules (e.g., “if obstacle ahead, turn left”). Example: Basic vacuum cleaner bots.

2. Model-Based Reflex Agents – Maintain an internal model of the world to handle partially observable environments. They update their model based on perception and act accordingly.

3. Goal-Based Agents – Make decisions by considering future actions that lead to a desired goal. They use search and planning to choose the best action.

4. Utility-Based Agents – Go beyond achieving goals by maximizing performance or utility. They evaluate multiple options and choose the one with the highest benefit.

5. Learning Agents – Improve performance over time by learning from past experiences, adapting strategies, and updating their knowledge base.

Summary:

• Simple Reflex → React instantly

• Model-Based → Use memory of the environment

• Goal-Based → Aim for specific objectives

• Utility-Based → Optimize outcomes

• Learning Agents → Continuously adapt and improve

These agent types form the foundation of intelligent system design in AI.

Read More:

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