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Hands-On Reinforcement Learning for Games

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Hands-On Reinforcement Learning for Games Micheal Lanham - okładka książki

Hands-On Reinforcement Learning for Games Micheal Lanham - okładka książki

Hands-On Reinforcement Learning for Games Micheal Lanham - okładka audiobooka MP3

Hands-On Reinforcement Learning for Games Micheal Lanham - okładka audiobooks CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
432
Dostępne formaty:
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     ePub
     Mobi

Ebook

129,00 zł

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Do przechowalni

With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python.

Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent's productivity. As you advance, you'll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games.

By the end of this book, you'll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications.

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Micheal Lanham - pozostałe książki

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