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Deep Reinforcement Learning in Action /

Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and advanced DRL techniques by taking on interesting challenges like navigating a maze and...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Brown, Brandon (Autor), Zai, Alexander (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Manning Publications, 2020.
Edición:1st edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and advanced DRL techniques by taking on interesting challenges like navigating a maze and playing video games. Along the way, you'll work with core algorithms, including deep Q-networks and policy gradients, along with industry-standard tools like PyTorch and OpenAI Gym. 
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650 0 |a Computational learning theory. 
650 0 |a Reinforcement learning. 
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650 6 |a Apprentissage par renforcement (Intelligence artificielle) 
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