This eBook introduces the concept of agentic AI, explaining its significance in the broader AI landscape and outlining the key concepts and applications that will be covered. It will highlight the book's value proposition for beginners and experienced readers alike.
Understanding Agentic AI
From Basics to Breakthroughs: Understanding AI Agents without the Complexity
Table of Contents:
Chapter 01 – Defining Agentic AI: Beyond Reactive Systems. This chapter clearly defines agentic AI, differentiating it from reactive and deliberative AI systems and exploring key characteristics like autonomy, goal-directed behavior, and proactive decision-making.
Chapter 02 – The Building Blocks: Algorithms and Architectures. This chapter delves into the essential building blocks of agentic AI, including machine learning algorithms, planning mechanisms, and knowledge representation techniques.
Chapter 03 – Real-World Applications: Agentic AI in Action. This chapter explores various real-world applications of agentic AI across different sectors, including robotics, autonomous vehicles, personalized assistants, and game AI.
Chapter 04 – Ethical Considerations: Navigating the Moral Landscape. This chapter focuses on the ethical considerations surrounding agentic AI, including issues such as bias, safety, accountability, job displacement, and the responsible development and deployment of autonomous systems.
Chapter 05 – Future Trends and Challenges: The Road Ahead. This chapter discusses emerging trends and future directions in agentic AI, examining potential breakthroughs and challenges and speculating on the future societal impact.
Conclusion – Actionable Insights and Next Steps. This final section summarizes key takeaways, provides actionable insights, and suggests areas for further exploration.