Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
DeepSeek R1: Building Collaborative Multi-Agent Systems for Real-World Tasks: A Hands-On Guide to Agent Design, Coordination, Communication Protocols,

DeepSeek R1: Building Collaborative Multi-Agent Systems for Real-World Tasks: A Hands-On Guide to Agent Design, Coordination, Communication Protocols,

Zhu, Yuan

Paperback

Series: Agentic AI and Graph-Powered Workflows Series: Practical Guides to Multi-Agent Systems, Langflow, R, Book 1

General Computers

ISBN13: 9798262502936
Publisher: Independently Published
Published: Aug 27 2025
Pages: 262
Weight: 1.01
Height: 0.55 Width: 7.00 Depth: 10.00
Language: English
DeepSeek R1 is a practical, example-first manual for building collaborative Multi-Agent Systems (MAS) that solve complex, distributed problems. Written for software engineers, AI practitioners, and systems architects, this book teaches modular agent design, inter-agent messaging protocols, negotiation and consensus strategies, task allocation, fault tolerance, and emergent behavior analysis. You'll learn how to integrate machine learning components supervised models, RL agents, and online learning into coordinated agent teams, plus how to containerize, orchestrate, and monitor multi-agent deployments with Docker, Kubernetes, and observability stacks (metrics, tracing, logging). Real projects warehouse robotics, fleet routing, environmental monitoring, and high-frequency decisioning show how to design for latency, throughput, and safety. Each of the 13 chapters includes runnable Python examples, architecture diagrams, debugging checklists, and performance tuning recipes.

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