Unlock the next era of software engineering—where intelligent, autonomous agents work alongside humans to reason, plan, collaborate, and take meaningful action.
As AI shifts from passive prediction to active autonomy, developers need a practical, end-to-end roadmap for building systems that are not just smart, but agentic. Building Intelligent AI Agents with Python provides exactly that.
Designed for engineers, researchers, and ambitious builders, this book demystifies the architecture, theory, and hands-on implementation of modern AI agents powered by Python and state-of-the-art language models. Through a comprehensive progression of core concepts, practical patterns, and real-world examples, you will learn how to create agents that observe, reason, decide, and act—independently or in coordinated teams.
You’ll start with foundational agent theory, including autonomy, perception, action, and historical evolution from early rule-based systems to today’s LLM-driven agents. From there, you’ll master the essential components that define truly intelligent agents: cognitive architectures, planning algorithms, tool-use frameworks, memory systems, multi-agent communication protocols, reinforcement learning, self-improving feedback loops, and more.
By the end, you’ll be ready to design everything from simple conversational assistants to sophisticated systems capable of multi-agent orchestration, collaboration, and adaptive problem-solving—all using Python’s rapidly growing ecosystem of agentic libraries.
What You’ll Learn
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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