Nayebi F. Foundations of Agentic AI for Retail. Concepts, Technologies,...2025

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Nayebi F. Foundations of Agentic AI for Retail. Concepts, Technologies,...2025

Textbook in PDF format Master Retail's Autonomous Future — Foundations of Agentic AI for Retail (Full-Color Edition) This book is the definitive, end-to-end playbook showing you how to design, code, and deploy autonomous agents that think, learn, and act in real time—transforming every aspect of your retail business. At its core, Agentic AI refers to AI systems — often called AI agents — that are capable of autonomously performing tasks on behalf of a user or another system by dynamically designing their own workflows and using available tools. It’s important to note that Agentic AI is not just Generative AI with a new name. While Generative AI (like ChatGPT) focuses on producing content in response to prompts, Agentic AI is goal-directed and can operate autonomously over extended periods. Agentic AI systems don’t necessarily require a prompt for each action; they can chain together sequences of decisions and actions to meet a higher-level objective. In other words, Generative AI is often reactive (it does something after you ask), whereas Agentic AI is proactive — it can initiate actions, adjust to changing conditions, and drive processes forward on its own. Agentic AI also tends to incorporate multiple AI techniques (LLMs, traditional algorithms, tools, etc.) to achieve precision in decision-making that pure generative models lack. This means an agentic system might generate content as one step, but it will also make choices, query databases, invoke APIs, or anything else required to reach its goal. In short, Agentic AI systems are designed for autonomous decision-making and action, giving them a novel form of digital agency beyond the capabilities of earlier AI approaches. Preface Introduction Part I: Foundations of Agentic AI Agent Architectures and Frameworks Decision‑Making Frameworks – Probabilistic Reasoning & Optimization Decision‑Making Frameworks – Sequential Decision‑Making Frameworks – RL & Planning Part II: Enabling Technologies and Architectures Foundation Models and Visual Intelligence Sensor Networks and Cognitive Systems Part III: Multi-Agent Systems and Integration End-to-End Integration for Autonomous Retail Part IV: Implementation and Ethical Considerations Implementing Agentic Systems in Retail Operational Excellence for AI Engineering in Retail Ethical Considerations and Governance Part V: Case Studies and Future Directions Real-World Case Studies Summary and Future Directions