Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more /

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This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL met...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Lapan, Maxim (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2018.
Temas:
Reinforcement learning.
Machine learning.
Natural language processing (Computer science)
Artificial intelligence.
Natural Language Processing
Artificial Intelligence
Machine Learning
Apprentissage par renforcement (Intelligence artificielle)
Apprentissage automatique.
Traitement automatique des langues naturelles.
Intelligence artificielle.
artificial intelligence.
COMPUTERS > General.
Artificial intelligence
Machine learning
Reinforcement learning
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ...
Notas:"Expert insight."
Descripción Física:1 online resource (1 volume) : illustrations
Bibliografía:Includes bibliographical references and index.
ISBN:9781788839303
1788839307
1788834240
9781788834247

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