Articoli correlati a Reinforcement Learning in the Ridesharing Marketplace
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This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.
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Informazioni sull?autore
Zhiwei (Tony) Qin, Ph.D., is a Principal Scientist at Lyft Rideshare Labs. He earned his Ph.D. from Columbia University. His research interests include operations research, machine learning, deep learning, and big data analytics, with applications in smart transportation and E-commerce.
Xiaocheng Tang, Ph.D., is an AI Research Scientist at Meta. He earned his Ph.D. from Lehigh University. His research interests lie at the intersection of machine learning, reinforcement learning, and optimization.
Qingyang Li, Ph.D., is a Senior Engineering Manager at DiDi Autonomous Driving. He earned his Ph.D. from Arizona State University. His research interests include machine learning, deep learning, reinforcement learning, and computer vision.
Jieping Ye, Ph.D. is affiliated with the Alibaba Group. He earned his Ph.D. from the University of Minnesota. His research interests include machine learning, data mining, artificial intelligence, transportation, and biomedical informatics.
Hongtu Zhu, Ph.D. is a Professor in the Department of Biostatics at The University of North Carolina at Chapel Hill. He earned his Ph.D. at The Chinese University of Hong Kong. His research interests include medical imaging analysis, imaging genetics, artificial intelligence, statistics, biostatics, and computational neuroscience.
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This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.
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Reinforcement Learning in the Ridesharing Marketplace (eng)
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Reinforcement Learning in the Ridesharing Marketplace (Synthesis Lectures on Learning, Networks, and Algorithms)
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Reinforcement Learning in the Ridesharing Marketplace
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Springer, Springer Aug 2025, 2025
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control. 144 pp. Englisch. Codice articolo 9783031596421
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Reinforcement Learning in the Ridesharing Marketplace (Synthesis Lectures on Learning, Networks, and Algorithms)
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Reinforcement Learning in the Ridesharing Marketplace (Synthesis Lectures on Learning, Networks, and Algorithms)
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Reinforcement Learning in the Ridesharing Marketplace
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Springer, Springer Aug 2025, 2025
ISBN 10: 3031596420
ISBN 13: 9783031596421
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 144 pp. Englisch. Codice articolo 9783031596421
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Reinforcement Learning in the Ridesharing Marketplace
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive overview of reinforcement learning for ridesharing applications. The authors first lay out the fundamentals of the ridesharing system architectures and review the basics of reinforcement learning, including the major applicable algorithms. The book describes the research problems associated with the various aspects of a ridesharing system and discusses the existing reinforcement learning approaches for solving them. The authors survey the existing research on each problem, and then examine specific case studies. The book also includes a review of two of methods closely related to reinforcement learning: approximate dynamic programming and model-predictive control. Codice articolo 9783031596421
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