Articles liés à Reinforcement Learning: Theory and Python Implementation
Synopsis
Reinforcement Learning: Theory and Python Implementation is a tutorial book on reinforcement learning, with explanations of both theory and applications. Starting from a uniform mathematical framework, this book derives the theory of modern reinforcement learning in a systematic way and introduces all mainstream reinforcement learning algorithms including both classical reinforcement learning algorithms such as eligibility trace and deep reinforcement learning algorithms such as PPO, SAC, and MuZero. Every chapter is accompanied by high-quality implementations based on the latest version of Python packages such as Gym, and the implementations of deep reinforcement learning algorithms are all with both TensorFlow 2 and PyTorch 1. All codes can be found on GitHub along with their results and are runnable on a conventional laptop with either Windows, macOS, or Linux.
This book is intended for readers who want to learn reinforcement learning systematically and applyreinforcement learning to practical applications. It is also ideal to academical researchers who seek theoretical foundation or algorithm enhancement in their cutting-edge AI research.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Zhiqing Xiao obtained doctoral degree from Tsinghua University in 2016 and has more than 15 years in academic research and industrial practices on data-analytics and AI. He is the author of two AI bestsellers in Chinese: "Reinforcement Learning" and "Application of Neural Network and PyTorch" and published many academic papers. He also contributed to recent versions of the open-source software Gym.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 68,62
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisRésultats de recherche pour Reinforcement Learning: Theory and Python Implementation
Image d'archives
Reinforcement Learning: Theory and Python Implementation
Edité par
Springer, 2024
ISBN 10 : 9811949328
ISBN 13 : 9789811949326
Ancien ou d'occasion
Couverture rigide
Vendeur : Books From California, Simi Valley, CA, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
hardcover. Etat : Acceptable. Back cover is partially torn. Pages are clean/intact. N° de réf. du vendeur mon0003786771
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Reinforcement Learning
Edité par
Springer Nature Singapore, 2024
ISBN 10 : 9811949328
ISBN 13 : 9789811949326
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces readers not only to algorithms, but also the mathematical theory behind themCovers all major reinforcement learning algorithms, including classical algorithms Every chapter is followed by high-quality implementations based on Pyt. N° de réf. du vendeur 628808139
Quantité disponible : Plus de 20 disponibles
Image d'archives
Reinforcement Learning: Theory and Python Implementation
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9789811949326_new
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Reinforcement Learning
Edité par
Springer Nature Singapore Sep 2024, 2024
ISBN 10 : 9811949328
ISBN 13 : 9789811949326
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Reinforcement Learning: Theory and Python Implementation is a tutorial book on reinforcement learning, with explanations of both theory and applications. Starting from a uniform mathematical framework, this book derives the theory of modern reinforcement learning systematically and introduces all mainstream reinforcement learning algorithms such as PPO, SAC, and MuZero. It also covers key technologies of GPT training such as RLHF, IRL, and PbRL. Every chapter is accompanied by high-quality implementations, and all implementations of deep reinforcement learning algorithms are with both TensorFlow and PyTorch. Codes can be found on GitHub along with their results and are runnable on a conventional laptop with either Windows, macOS, or Linux.This book is intended for readers who want to learn reinforcement learning systematically and apply reinforcement learning to practical applications. It is also ideal to academical researchers who seek theoretical foundation or algorithm enhancement in their cutting-edge AI research. 584 pp. Englisch. N° de réf. du vendeur 9789811949326
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Reinforcement Learning
Edité par
Springer Nature Singapore, Springer Nature Singapore Sep 2024, 2024
ISBN 10 : 9811949328
ISBN 13 : 9789811949326
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Neuware -Reinforcement Learning: Theory and Python Implementation is a tutorial book on reinforcement learning, with explanations of both theory and applications. Starting from a uniform mathematical framework, this book derives the theory of modern reinforcement learning systematically and introduces all mainstream reinforcement learning algorithms such as PPO, SAC, and MuZero. It also covers key technologies of GPT training such as RLHF, IRL, and PbRL. Every chapter is accompanied by high-quality implementations, and all implementations of deep reinforcement learning algorithms are with both TensorFlow and PyTorch. Codes can be found on GitHub along with their results and are runnable on a conventional laptop with either Windows, macOS, or Linux.This book is intended for readers who want to learn reinforcement learning systematically and apply reinforcement learning to practical applications. It is also ideal to academical researchers who seek theoretical foundation or algorithm enhancement in their cutting-edge AI research.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 584 pp. Englisch. N° de réf. du vendeur 9789811949326
Quantité disponible : 2 disponible(s)
Image d'archives
Reinforcement Learning: Theory and Python Implementation
Vendeur : California Books, Miami, FL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur I-9789811949326
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Reinforcement Learning : Theory and Python Implementation
Edité par
Springer Nature Singapore, Springer Nature Singapore, 2024
ISBN 10 : 9811949328
ISBN 13 : 9789811949326
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Reinforcement Learning: Theory and Python Implementation is a tutorial book on reinforcement learning, with explanations of both theory and applications. Starting from a uniform mathematical framework, this book derives the theory of modern reinforcement learning systematically and introduces all mainstream reinforcement learning algorithms such as PPO, SAC, and MuZero. It also covers key technologies of GPT training such as RLHF, IRL, and PbRL. Every chapter is accompanied by high-quality implementations, and all implementations of deep reinforcement learning algorithms are with both TensorFlow and PyTorch. Codes can be found on GitHub along with their results and are runnable on a conventional laptop with either Windows, macOS, or Linux.This book is intended for readers who want to learn reinforcement learning systematically and apply reinforcement learning to practical applications. It is also ideal to academical researchers who seek theoretical foundation or algorithm enhancement in their cutting-edge AI research. N° de réf. du vendeur 9789811949326
Quantité disponible : 1 disponible(s)
Image d'archives
Reinforcement Learning : Theory and Python Implementation
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 46076898-n
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Reinforcement Learning : Theory and Python Implementation
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur 46076898-n
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Reinforcement Learning : Theory and Python Implementation
Edité par
Springer, 2024
ISBN 10 : 9811949328
ISBN 13 : 9789811949326
Ancien ou d'occasion
Couverture rigide
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 46076898
Quantité disponible : Plus de 20 disponibles