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Deep Reinforcement Learning Hands-On - Second Edition

Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more

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  • 826 Seiten
  • 29 Lesestunden

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This updated guide delves into deep reinforcement learning, showcasing its applications in addressing intricate real-world challenges. The new edition features expanded content on multi-agent methods, discrete optimization, and the role of reinforcement learning in robotics. Additionally, it covers advanced exploration techniques, making it a comprehensive resource for both beginners and experienced practitioners seeking to deepen their understanding of this rapidly evolving field.

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Deep Reinforcement Learning Hands-On - Second Edition, Maxim Lapan

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Erscheinungsdatum
2020
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