| 書(shū)目名稱(chēng) | Fundamentals of Reinforcement Learning | | 編輯 | Rafael Ris-Ala | | 視頻video | http://file.papertrans.cn/351/350516/350516.mp4 | | 概述 | Enables rapid development of Reinforcement Learning skills.Includes step-by-step operations of the most used algorithms for developing solutions in RL.Introduces AI, Machine Learning techniques, and e | | 圖書(shū)封面 |  | | 描述 | .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. | | 出版日期 | Textbook 2023 | | 關(guān)鍵詞 | Q-Learning Algorithm; Deep Learning; Machine Learning; Artificial Intelligence; Markov Chain | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-37345-9 | | isbn_softcover | 978-3-031-37347-3 | | isbn_ebook | 978-3-031-37345-9 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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