Agentic RAG explores the evolution of Retrieval-Augmented Generation (RAG) into intelligent AI systems that can reason, plan, retrieve knowledge, use external tools, and continuously improve their responses. The book begins with the fundamentals of traditional RAG, its architecture, and its limitations, before introducing Agentic RAG as a more autonomous and adaptive approach. It explains how AI agents understand user intent, rewrite and decompose complex queries, select appropriate knowledge sources, and perform multi-stage retrieval. The book also covers reasoning loops, planning strategies, dynamic tool selection, iterative search, self-correction, and memory management, including short-term, long-term, and semantic memory. Readers will learn how to verify retrieved evidence, reduce hallucinations, implement security guardrails, and evaluate system performance. Finally, the book focuses on building production-ready applications using scalable architectures, multi-agent collaboration, knowledge graphs, and multimodal retrieval.
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Taschenbuch. Condition: Neu. Agentic Retrieval-Augmented Generation | Building AI that Searches, Reasons and Acts | Vishwanil Suman (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630401028 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 138100543