Hands-On Reinforcement Learning for Games

Lanham, Micheal

  • 出版商: Packt Publishing
  • 出版日期: 2020-01-03
  • 售價: $1,380
  • 貴賓價: 9.5$1,311
  • 語言: 英文
  • 頁數: 432
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1839214937
  • ISBN-13: 9781839214936
  • 相關分類: ReinforcementDeepLearning
  • 立即出貨 (庫存=1)

買這商品的人也買了...

商品描述

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.

商品描述(中文翻譯)




隨著人工智慧在遊戲行業中的增加,開發人員面臨著將人工智慧整合到項目中,創建高度響應和適應性遊戲的挑戰。本書將指導您學習如何使用Python在遊戲開發中應用各種強化學習技術和算法。

 

從基礎知識開始,本書將幫助您在遊戲開發中建立強化學習的堅實基礎。每一章都將協助您實施不同的強化學習技術,例如馬爾可夫決策過程(MDPs)、Q學習、演員評論方法、SARSA和確定性策略梯度算法,以建立邏輯自學代理。學習這些技術將增強您的遊戲開發技能,並添加各種功能以提高遊戲代理的生產力。隨著您的進步,您將了解如何使用深度強化學習(DRL)技術制定策略,幫助代理從其行動中學習並建立引人入勝的遊戲。

 

通過閱讀本書,您將準備好應用強化學習技術來構建各種項目並為開源應用做出貢獻。




作者簡介

Micheal Lanham is a proven software and tech innovator with 20 years of experience. During that time, he has developed a broad range of software applications in areas such as games, graphics, web, desktop, engineering, artificial intelligence, GIS, and machine learning applications for a variety of industries as an R&D developer. At the turn of the millennium, Micheal began working with neural networks and evolutionary algorithms in game development. He was later introduced to Unity and has been an avid developer, consultant, manager, and author of multiple Unity games, graphic projects, and books ever since.

作者簡介(中文翻譯)

Micheal Lanham是一位經驗豐富的軟體和科技創新者,擁有20年的經驗。在這段時間裡,他作為研發開發人員,在遊戲、圖形、網頁、桌面、工程、人工智慧、地理資訊系統和機器學習等領域開發了各種軟體應用程式,並為多個行業提供了解決方案。在千禧年之際,Micheal開始在遊戲開發中使用神經網絡和演化算法。後來,他接觸到Unity並成為一位熱衷的開發者、顧問、經理和多本Unity遊戲、圖形項目和書籍的作者。