Generative AI Series

Multi-Agent System

Multi-Agent systems are LLM applications that are changing the automation landscape with intelligent bots.

This blog is an ongoing series on Generative AI and introduction to multi-agent architecture and frameworks such as Autogen, Crew.ai, that help build intelligent bots, that implement multi-agent architectures.

Multi-Agent System: An Overview

In the context of language models and AI, a multi-agent system involves multiple independent actors, each powered by language models, collaborating in a specific way. These agents have their own persona/role, and a context that is define by the prompts on a specific language model. Each agent has access to various tools, to help execute the task given to the agent. Multiple agents bring different perspectives and helps make better decisions.

Multi-agent systems differ from single-agent systems primarily in the distribution of decision-making and interaction within a system. In a single-agent system, a centralized agent makes all decisions, while other agents act as remote slaves. This single agent, normally decides, based on the context. This might miss out the other perspectives/possibilities. On the other hand, multi-agent systems involve multiple interacting intelligent agents, each capable of making decisions and influencing the environment.