Multi Agent Reinforcement Learning Handbook (Paperback)

Language: English

Published by Independently Published, 2026

9798196756610

Series: Book 4 of 12 - Programming AI & Development Handbook Collection

  • Softcover
  • New
See all details

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

5-star seller

AbeBooks seller since October 12, 2005

View this seller's items
Softcover

Condition: New

US$ 24.99

 Free Shipping 
Ships within U.S.A.

Quantity: 1 available

Add to basket
Free 30-day returns

Item description from seller

Paperback. The Final Frontier of AI is Collaborative.The era of isolated AI is over. From autonomous warehouse swarms and smart energy grids to decentralized finance and cooperative robotics, the future belongs to systems that can communicate, coordinate, and compete. But scaling reinforcement learning from a single agent to a collective of intelligent actors introduces a chaotic new world of non-stationarity and coordination failure.The Multi-Agent Reinforcement Learning Handbook is your definitive blueprint for navigating this complexity.Written for senior AI engineers, researchers, and data scientists, this handbook cuts through the academic noise to provide a hands-on, implementation-first guide to MARL. You won't just learn the theory; you will master the architectures-like QMIX, MAPPO, and Multi-Agent Transformers-that allow agents to thrive in decentralized environments.What You Will Master: The Fundamentals of Cooperation: Master the Dec-POMDP framework and learn how to solve the "Moving Target" problem in non-stationary environments.Value Factorization & Credit Assignment: Deep dive into VDN and QMIX to understand how individual agent contributions are distilled from a collective team reward.Policy Optimization at Scale: Implement state-of-the-art algorithms like MAPPO and explore the cutting-edge Multi-Agent Transformer (MAT).Emergent Communication: Learn how agents "invent" their own languages and protocols to solve tasks through differentiable communication channels.Offline MARL & Safety: Discover how to train collaborative agents from static datasets using Conservative Q-Learning (CQL) and ensure human-AI alignment.The Transformers & Diffusion Frontier: Explore the 2026 vanguard, including trajectory stitching with Diffusion models and the role of LLMs in agent reasoning.Why This Book?In just 137 concise, high-impact pages, Sammy Tech distills years of research and industrial application into a focused mastery guide. Leveraging the power of Python and PyTorch 2.x, this handbook provides the code-heavy, logic-driven approach necessary to build production-ready collaborative AI.Whether you are building the next generation of autonomous traffic control or designing complex ad-hoc teamwork protocols, this book is your essential companion on the road to MARL mastery.Architect the future of collective intelligence. Order your copy today. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Seller Inventory # 9798196756610

Title
Multi Agent Reinforcement Learning Handbook (Paperback)
Author
Sammy Tech
Publisher
Independently Published
Publication year
2026
Condition
new
Binding
Paperback
Language
English
ISBN 13
9798196756610
Series
Book 4 of 12: Programming AI & Development Handbook Collection

Grand Eagle Retail

Bensenville, IL, U.S.A.

5-star seller

AbeBooks seller since October 12, 2005

Shipping rates within U.S.A.

Item6 to 14 business days6 to 16 business days
First itemUS$ 0.00US$ 0.00
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

  • Visa
  • Mastercard
  • American Express
  • Apple Pay
  • Google Pay

Seller's business information

APOLLO ONLINE CORP.

605 Geddes Street
Wilmington, DE U.S.A. 19805