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.


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Table Of Contents

  1. Chapter 01: Defining Agentic AI: Beyond Reactive Systems - Delving into the core characteristics that distinguish agentic AI from other AI types.
    This chapter will clearly define agentic AI, differentiating it from reactive and deliberative AI systems. It will explore key characteristics like autonomy, goal-directed behavior, and proactive decision-making, providing concrete examples to illustrate these concepts.

  2. Chapter 02: The Building Blocks: Algorithms and Architectures - Exploring the fundamental components that empower agentic AI.
    This chapter will delve into the essential building blocks of agentic AI, including machine learning algorithms (reinforcement learning, supervised learning), planning mechanisms (search algorithms, hierarchical planning), and knowledge representation techniques (knowledge graphs, ontologies). The role of each component in enabling agentic behavior will be explained.

  3. Chapter 03: Real-World Applications: Agentic AI in Action - Showcasing diverse examples of agentic AI across various industries.
    This chapter will explore various real-world applications of agentic AI across different sectors, including robotics, autonomous vehicles, personalized assistants, and game AI. Case studies will illustrate the practical impact and benefits of agentic AI.

  4. Chapter 04: Ethical Considerations: Navigating the Moral Landscape - Addressing the ethical challenges and responsibilities associated with agentic AI.
    This chapter will focus 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. It will explore best practices and frameworks for ethical AI development.

  5. Chapter 05: Future Trends and Challenges: The Road Ahead - Exploring the potential future developments and obstacles in the field of agentic AI.
    This chapter will discuss emerging trends and future directions in agentic AI, examining potential breakthroughs and challenges. It will explore the long-term societal impact and speculate on the future of this transformative technology.

  6. Conclusion: Actionable Insights and Next Steps - Summarizing key takeaways, providing actionable insights, and suggesting further exploration.