Több mint 10 millió cím angol és más nyelveken! Fedezd fel új történetedet még ma!

Deep Multi-Agent Reinforcement Learning

Name: Deep Multi-Agent Reinforcement Learning
Brand: Independently published
SKU: 9798185265246
Price: 12866 HUF
Availability: InStock

Algorithms, Cooperation, Competition, Communication Learning, Graph Neural Networks, and Large-Scale Multi-Agent Decision Making

Szerző: Julian Stonemere

Nyelv:

Kötés: Puha kötésű

Kiadó: Independently published

Elérhetőség: Beszállítói készleten

Küldés 9-13 napon belül

12 866 Ft

Your first multi-agent RL project will teach you a hard truth: everything you know about single-agen...

Információk a könyvről

Szerző

Julian Stonemere

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2026

oldal

260

EAN

9798185265246

Enbook ID

53200011

Kiadó

Independently published

Súly

458

Méretek

178 x 254 x 14

Teljes leírás

Your first multi-agent RL project will teach you a hard truth: everything you know about single-agent training breaks the moment a second learner enters the room.
Non-stationarity sets in. Rewards stop meaning what you think they mean. And the fixes that worked for a single policy quietly make things worse.
This is the book for engineers and researchers who already know single-agent RL and are ready for what comes next - written by a practitioner who's built coordinating robot fleets, adversarial trading agents, and cooperating LLM agent teams, and who still remembers exactly where it went wrong the first time.
Inside, you'll learn:

Why non-stationarity is the real enemy of MARL - and how to design around it
How to formulate state, observation, action, and reward before you write training code (the highest-leverage decision in any MARL project)
Cooperative methods: value decomposition (VDN, QMIX), credit assignment, and learned communication
Competitive methods: self-play, opponent modeling, exploitability, and why average return lies to you
Scaling to dozens or hundreds of agents without training collapsing
Graph neural networks, mean-field methods, and attention-based communication architectures
Real deployment: sim-to-real transfer, robotics, swarms, and multi-agent LLM systems
Where the field is still unsolved - continual learning, human-AI teams, and multi-agent alignment

Written in first person, with real mistakes included, not just the theory that made it into the papers. Every chapter builds a working intuition, then shows you exactly how it fails in practice - so you find out in the book, not three weeks into a training run.
If you've trained a MARL system, watched it behave strangely, and wanted to know why - this book is for you.

Leggyakrabban keresett

Categories

Authors

Publishers

Termékek

Termékek

Leggyakrabban keresett

Categories

Authors

Publishers

Termékek

Termékek

Deep Multi-Agent Reinforcement Learning

Algorithms, Cooperation, Competition, Communication Learning, Graph Neural Networks, and Large-Scale Multi-Agent Decision Making

Információk a könyvről

Teljes leírás

Érdekelheti

Azok a vásárlók, akik ezt a könyvet megvásárolták, a következőket is megvásárolták