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Fundamentals of Reinforcement Learning / by Rafael Ris-Ala

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Cham : Springer Nature Switzerland : Imprint: Springer)
出版年	2023
大きさ	XV, 88 p. 94 illus., 87 illus. in color : online resource
著者標目	*Ris-Ala, Rafael author SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0002917	Computer Scinece R0 2005-6,2022-3				9783031373459

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一般注記	Chapter. 1. Introduction -- Chapter. 2. Concepts -- Chapter. 3. Q-Learning algorithm -- Chapter. 4. Development tools -- Chapter. 5. Practice with code -- Chapter. 6. Recent applications and future research -- Index Artificial intelligence (AI) applications bring agility and modernity to our lives, and the reinforcement learning technique is at the forefront of this technology. It can outperform human competitors in strategy games, creative compositing, and autonomous movement. Moreover, it is just starting to transform our civilization. This book provides an introduction to AI, specifies machine learning techniques, and explores various aspects of reinforcement learning, approaching the latest concepts in a didactic and illustrated manner. It is aimed at students who want to be part of technological advances and professors engaged in the development of innovative applications, helping with academic and industrial challenges. Understanding the Fundamentals of Reinforcement Learning will allow you to: Understand essential AI concepts Gain professional experience Interpret sequential decision problems and solve them with reinforcement learning Learn how the Q-Learning algorithm works Practice with commented Python code Find advantageous directions HTTP:URL=https://doi.org/10.1007/978-3-031-37345-9
件　名	LCSH:Machine learning LCSH:Artificial intelligence LCSH:Software engineering FREE:Machine Learning FREE:Artificial Intelligence FREE:Software Engineering
分　類	LCC:Q325.5-.7 DC23:006.31
書誌ID	EB00002305
ISBN	9783031373459