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Reinforcement Learning in the Ridesharing Marketplace
Buch von Zhiwei Qin (u. a.)
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor

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.

Inhaltsverzeichnis

Introduction.- Ridesharing.- Reinforcement Learning Prime.- Pricing & Incentives.- Online Matching.- Vehicle Repositioning.- Routing.- Ride-pooling.- Related Methods.- Open Resources.- Challenges and Opportunities.- Closing Remarks.

Details
Erscheinungsjahr: 2024
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Reihe: Synthesis Lectures on Learning, Networks, and Algorithms
Inhalt: vii
133 S.
2 s/w Illustr.
26 farbige Illustr.
133 p. 28 illus.
26 illus. in color.
ISBN-13: 9783031596391
ISBN-10: 3031596390
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Qin, Zhiwei (Tony)
Tang, Xiaocheng
Ye, Jieping
Zhu, Hongtu
Li, Qingyang
Hersteller: Springer International Publishing
Springer International Publishing AG
Synthesis Lectures on Learning, Networks, and Algorithms
Maße: 246 x 173 x 14 mm
Von/Mit: Zhiwei Qin (u. a.)
Erscheinungsdatum: 04.08.2024
Gewicht: 0,43 kg
Artikel-ID: 128860679
Über den Autor

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.

Inhaltsverzeichnis

Introduction.- Ridesharing.- Reinforcement Learning Prime.- Pricing & Incentives.- Online Matching.- Vehicle Repositioning.- Routing.- Ride-pooling.- Related Methods.- Open Resources.- Challenges and Opportunities.- Closing Remarks.

Details
Erscheinungsjahr: 2024
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Reihe: Synthesis Lectures on Learning, Networks, and Algorithms
Inhalt: vii
133 S.
2 s/w Illustr.
26 farbige Illustr.
133 p. 28 illus.
26 illus. in color.
ISBN-13: 9783031596391
ISBN-10: 3031596390
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Qin, Zhiwei (Tony)
Tang, Xiaocheng
Ye, Jieping
Zhu, Hongtu
Li, Qingyang
Hersteller: Springer International Publishing
Springer International Publishing AG
Synthesis Lectures on Learning, Networks, and Algorithms
Maße: 246 x 173 x 14 mm
Von/Mit: Zhiwei Qin (u. a.)
Erscheinungsdatum: 04.08.2024
Gewicht: 0,43 kg
Artikel-ID: 128860679
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