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What is Multi-agent?

It is the collaboration of more than one artificial intelligence software for a common goal by dividing a complex task.

Overview

In multi-agent systems, each artificial intelligence agent acts as an employee with its own area of ​​expertise. While one agent plans, another writes code, and another checks the results. In this way, tasks that a single model would have difficulty doing alone are completed much faster and without errors in cooperation.

Analogy: Instead of a single person trying to manage the entire company, it is like a team specialized in different departments coming together and working on the project.

How it works

Define one main task and divide it into sub-parts. Assign an agent with special abilities to each piece. Manage the process by ensuring that these agents communicate with each other.

Where it is used

It is frequently used in software development, complex data analysis and automated workflows.

Commonly confused with

It is different from a single AI model; What is important here is the interaction of the agents with each other.

Frequently asked questions

How do agents get along?

They usually message via a 'conductor' agent or a predetermined communication protocol.

Why don't we use a single powerful model?

When tasks become very complex, smaller specialized models combine to make fewer errors and produce better results.

Related terms

Related tools

This explanation was written in plain language for TreScout and machine-translated from the Turkish original · the Turkish version prevails. If something looks wrong or missing, write to hello@trescout.com. Read in Turkish →