marl-book
"A landmark textbook to multiagent reinforcement learning, combining game-theoretic foundations with state-of-the-art deep learning. This essential textbook delivers fundamental insights for newcomers, experts and practitioners, featuring real-world applications and advanced algorithms."
GitHub - marl-book/slides: Lecture slides for the MARL book (www.marl ...
This repository contains slides for the MIT Press textbook "Multi-Agent Reinforcement Learning: Foundations and Modern Approaches" by Stefano V. Albrecht, Filippos Christianos, and Lukas Schäfer. The book can be freely accessed on this webpage: www.marl-book.com. Lecture recordings from a summer course using the slides are available on YouTube.
“This book is the first complete reference for the growing area of multi-agent rein- forcement learning. It provides both an essential resource for newcomers to the field;
GitHub - marl-book/codebase: Official code repo for the MARL book …
This codebase accompanies the MARL book and provides access to basic and easy-to-understand MARL ideas. The algorithms are self-contained and the implementations are focusing on simplicity.
Multi-Agent Reinforcement Learning - MIT Press
Dec 17, 2024 · Building from foundational ideas and incorporating recent breakthroughs in deep learning, this book will help accelerate theoretical and practical progress. The first comprehensive introduction to Multi-Agent Reinforcement Learning (MARL), covering MARL's models, solution concepts, algorithmic ideas, technical ch...
Multi-Agent Reinforcement Learning: Foundations and Modern …
Dec 17, 2024 · The book first introduces the field’s foundations, including basics of reinforcement learning theory and algorithms, interactive game models, different solution concepts for games, and the algorithmic ideas underpinning MARL research.
Standard MARL books? : r/reinforcementlearning - Reddit
Jan 13, 2023 · There is a new MIT Press textbook "Multi-Agent Reinforcement Learning: Foundations and Modern Approaches" by Stefano V. Albrecht, Filippos Christianos, and Lukas Schäfer. The PDF can be downloaded here: https://www.marl-book.com. This github link might help: https://github.com/LantaoYu/MARL-Papers.
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