What is a Multi-Agent System (vs. a Single Agent)?

A single AI agent is an autonomous program that can make decisions and act to achieve goals in some environment, essentially working on its own. By contrast, a multi-agent system (MAS) uses multiple agents working together and interacting within a common environment. These agents might cooperate on a shared goal or pursue individual goals that impact each other. The key difference is that they communicate and coordinate their actions, instead of operating in isolation.

Think of a single agent as a skilled solo worker, whereas a multi-agent system is more like a well-coordinated team. Just as a team can divide up a big project into specialized roles, a multi-agent system allows specialized agents to tackle different parts of a complex task in parallel and share their results.

Scenarios Where Multi-Agent Systems Make Sense

1. Increasing Complexity of Tasks

2. Diverse Expertise Required

3. Parallelism and Speed

4. Scalability and Distribution

5. Naturally Multi-Entity Problems