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Multi-Agent Reinforcement Learning

- Foundations and Modern Approaches
Af: Stefano V. Albrecht, Filippos Christianos Engelsk Hardback

Multi-Agent Reinforcement Learning

- Foundations and Modern Approaches
Af: Stefano V. Albrecht, Filippos Christianos Engelsk Hardback
Tjek vores konkurrenters priser
The first comprehensive introduction to Multi-Agent Reinforcement Learning (MARL), covering MARL’s models, solution concepts, algorithmic ideas, technical challenges, and modern approaches.

Multi-Agent Reinforcement Learning (MARL), an area of machine learning in which a collective of agents learn to optimally interact in a shared environment, boasts a growing array of applications in modern life, from autonomous driving and multi-robot factories to automated trading and energy network management. This text provides a lucid and rigorous introduction to the models, solution concepts, algorithmic ideas, technical challenges, and modern approaches in MARL. 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. It then details contemporary MARL algorithms which leverage deep learning techniques, covering ideas such as centralized training with decentralized execution, value decomposition, parameter sharing, and self-play. The book comes with its own MARL codebase written in Python, containing implementations of MARL algorithms that are self-contained and easy to read. Technical content is explained in easy-to-understand language and illustrated with extensive examples, illuminating MARL for newcomers while offering high-level insights for more advanced readers.

  • First textbook to introduce the foundations and applications of MARL, written by experts in the field
  • Integrates reinforcement learning, deep learning, and game theory
  • Practical focus covers considerations for running experiments and describes environments for testing MARL algorithms
  • Explains complex concepts in clear and simple language
  • Classroom-tested, accessible approach suitable for graduate students and professionals across computer science, artificial intelligence, and robotics 
  • Resources include code and slides 
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Tjek vores konkurrenters priser
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Tjek vores konkurrenters priser
The first comprehensive introduction to Multi-Agent Reinforcement Learning (MARL), covering MARL’s models, solution concepts, algorithmic ideas, technical challenges, and modern approaches.

Multi-Agent Reinforcement Learning (MARL), an area of machine learning in which a collective of agents learn to optimally interact in a shared environment, boasts a growing array of applications in modern life, from autonomous driving and multi-robot factories to automated trading and energy network management. This text provides a lucid and rigorous introduction to the models, solution concepts, algorithmic ideas, technical challenges, and modern approaches in MARL. 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. It then details contemporary MARL algorithms which leverage deep learning techniques, covering ideas such as centralized training with decentralized execution, value decomposition, parameter sharing, and self-play. The book comes with its own MARL codebase written in Python, containing implementations of MARL algorithms that are self-contained and easy to read. Technical content is explained in easy-to-understand language and illustrated with extensive examples, illuminating MARL for newcomers while offering high-level insights for more advanced readers.

  • First textbook to introduce the foundations and applications of MARL, written by experts in the field
  • Integrates reinforcement learning, deep learning, and game theory
  • Practical focus covers considerations for running experiments and describes environments for testing MARL algorithms
  • Explains complex concepts in clear and simple language
  • Classroom-tested, accessible approach suitable for graduate students and professionals across computer science, artificial intelligence, and robotics 
  • Resources include code and slides 
Vis mere
Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 394
ISBN-13: 9780262049375
Indbinding: Hardback
Udgave:
ISBN-10: 0262049376
Kategori: Informationsteknologi: generelt
Udg. Dato: 17 dec 2024
Længde: 30mm
Bredde: 236mm
Højde: 161mm
Forlag: MIT Press Ltd
Oplagsdato: 17 dec 2024
Forfatter(e): Stefano V. Albrecht, Filippos Christianos
Forfatter(e) Stefano V. Albrecht, Filippos Christianos

Kategori Informationsteknologi: generelt

ISBN-13 9780262049375

Sprog Engelsk

Indbinding Hardback

Sider 394

Udgave

Længde 30mm

Bredde 236mm

Højde 161mm

Udg. Dato 17 dec 2024

Oplagsdato 17 dec 2024

Forlag MIT Press Ltd