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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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Anjanava Biswas Anjanava Biswas
Author Profile Icon Anjanava Biswas
Anjanava Biswas
Wrick Talukdar Wrick Talukdar
Author Profile Icon Wrick Talukdar
Wrick Talukdar
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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

Exploring the architecture of agentic systems

Agentic systems, designed for executing complex goals in an autonomous way, can be implemented using a good variety of architectural patterns. In general, these patterns define the structure and the behavior that allows the system to perceive, reason, learn, and act upon the environment in an effective way. Three main architectural patterns for agentic systems are deliberative, reactive, and hybrid architectures. Let’s discuss them in detail.

Deliberative architectures

Also known as knowledge-based or symbolic architectures, rely on the use of explicit representations of knowledge and reasoning mechanisms to reach decisions. They typically follow a sense-plan-act cycle, where they first perceive information about the environment, then make a plan of action according to that perception and the knowledge base, and finally execute such plans of action.

The key advantage of deliberative architectures is their ability to handle...

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