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Building Agentic AI Systems

You're reading from   Building Agentic AI Systems Create intelligent, autonomous AI agents that can reason, plan, and adapt

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Product type Paperback
Published in Apr 2025
Publisher Packt
ISBN-13 9781803238753
Length 288 pages
Edition 1st Edition
Concepts
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Authors (2):
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Wrick Talukdar Wrick Talukdar
Author Profile Icon Wrick Talukdar
Wrick Talukdar
Anjanava Biswas Anjanava Biswas
Author Profile Icon Anjanava Biswas
Anjanava Biswas
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Foundations of Generative AI and Agentic Systems
2. Chapter 1: Fundamentals of Generative AI FREE CHAPTER 3. Chapter 2: Principles of Agentic Systems 4. Chapter 3: Essential Components of Intelligent Agents 5. Part 2: Designing and Implementing Generative AI-Based Agents
6. Chapter 4: Reflection and Introspection in Agents 7. Chapter 5: Enabling Tool Use and Planning in Agents 8. Chapter 6: Exploring the Coordinator, Worker, and Delegator Approach 9. Chapter 7: Effective Agentic System Design Techniques 10. Part 3: Trust, Safety, Ethics, and Applications
11. Chapter 8: Building Trust in Generative AI Systems 12. Chapter 9: Managing Safety and Ethical Considerations 13. Chapter 10: Common Use Cases and Applications 14. Chapter 11: Conclusion and Future Outlook 15. Index 16. Other Books You May Enjoy

Understanding multi-agent systems

Multi-agent systems (MASs) represent an important subfield of the broader area of distributed artificial intelligence. They consist of several intelligent agents that interact, cooperate, and coordinate with each other to execute tasks and achieve collective goals. Each agent in a MAS is typically autonomous, capable of perceiving its environment through sensors, possessing a reasoning mechanism to make decisions, and acting upon those decisions to meet its design objectives. The collective behavior and interactions of these agents enable MASs to tackle complex problems that single-agent systems struggle with due to the inherent limitations of individual agents.

Examples of MASs can be found in various domains, demonstrating their applicability and effectiveness in solving complex problems:

  • Supply chain management and logistics: MASs can be used to optimize supply chain operations by coordinating the activities of different agents representing...
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