Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Constrained Control and Machine Learning: Emerging Methodologies and Applications

Constrained Control and Machine Learning: Emerging Methodologies and Applications

Fortino, Giancarlo
Franzè, Giuseppe
Lucia, Walter

Hardcover

Series: Internet of Things

Technology & EngineeringGeneral ComputersProbability & Statistics

PREORDER - Expected ship date January 18, 2026

ISBN10: 303202708X
ISBN13: 9783032027085
Publisher: Springer
Published: Jan 18 2026
Pages: 140
Language: English

This book addresses the use of constrained control and machine learning approaches within data-driven settings in the field of autonomous robots for Industry 5.0 and Intelligent Transportation Systems. The primary aim of the book is to highlight the strict connection between constrained control and machine learning when tackling real-like phenomena in terms of a data-driven framework. The book shows how constrained control techniques and machine learning approaches can be adequately combined to derive novel and more efficient hybrid control architectures for data-driven based scenarios. To this end, several control problems ranging from planning and formation of autonomous multi-vehicles, routing decisions in urban road networks, freeway traffic modeling, to autonomous robotics in healthcare, are considered to highlight the capability of the data-driven approach to combine techniques coming from different research domains. The book is mainly devoted to researchers that, starting from a solid expertise on the constrained control and/or machine learning tools, would improve their ability to jointly use these technicalities in the data-driven setting.

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