1 Understanding multi-agent systems

 

This chapter covers

  • An introduction to multi-agent systems and the type of problems (complex tasks) for which they provide value
  • A discussion on components of a multi-agent application
  • An overview of AutoGen, a framework for building multi-agent Generative AI applications

1.1 What is a Multi-Agent System (MAS)?

1.2 Why use multiple agents? A complex task perspective

1.2.1 Planning

1.2.2 Diverse Expertise

1.2.3 Extensive Context

1.2.4 Adaptive Solutions

1.3 Why Now?

1.3.1 Advances in Generative AI Reasoning Capabilities

1.3.2 Opportunity to Innovate in Addressing Tacit Knowledge Tasks

1.3.3 Increasing Demand for Reliable Automation

1.3.4 Ethical AI Deployment

1.4 Patterns in Building Multi-Agent Systems

1.4.1 Agent Pipelines (Chains)

1.4.2 Autonomous Multi-Agent Collaboration

1.5 Components of a Multi-Agent System

1.5.1 Component Terminology and Definitions

1.5.2 Agent Driver (Generative AI Model)

1.5.3 Tools / Skills / Plugins

1.5.4 Memory

1.5.5 Plans

1.5.6 Orchestration Patterns

1.5.7 Workflow

1.6 AutoGen - A framework for building Multi-Agent Systems

1.6.1 AutoGen Core Features

1.6.2 A Basic Example

1.7 When to and when not to use a Multi-Agent Approach

1.8 Summary

1.9 References