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Beschreibung
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
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
Über den Autor
Rafael Ris-Ala José Jardim is a professor and researcher in Machine Learning and Research Methodology at the Federal University of Rio de Janeiro (UFRJ) and at Faculdade XP Educação (XPE). He holds a master's degree in Data Science from UFRJ and is currently pursuing his Ph.D. in Artificial Intelligence at the same institution.
He is the author of several articles on Software Engineering and has supervised more than 50 academic papers. He is a recognized journal reviewer for Elsevier and Clarivate and participates in reviewing IEEE scientific papers.
He served as Infrastructure Project Manager at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) and was responsible for creating a Data Center. He has more than 10 years of experience in Software Development in the Brazilian Navy.
Inhaltsverzeichnis

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.

Details
Erscheinungsjahr: 2024
Genre: Informatik, Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xv
88 S.
7 s/w Illustr.
87 farbige Illustr.
88 p. 94 illus.
87 illus. in color.
ISBN-13: 9783031373473
ISBN-10: 3031373472
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Ris-Ala, Rafael
Hersteller: Springer
Birkhäuser
Springer International Publishing AG
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 7 mm
Von/Mit: Rafael Ris-Ala
Erscheinungsdatum: 17.08.2024
Gewicht: 0,172 kg
Artikel-ID: 129957559

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