Articoli correlati a Engineering the Future: AI, Optimization, and the Evolution...
Risultati della ricerca per Engineering the Future: AI, Optimization, and the Evolution...
Foto dell'editore
UNKNOWN
ISBN 13: 9798295423116
Antico o usato
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: As New. Unread book in perfect condition. Codice articolo 51809446
Compra usato
EUR 22,62
Spedizione EUR 2,30
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
UNKNOWN
ISBN 13: 9798295423116
Nuovo
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 51809446-n
Compra nuovo
EUR 22,77
Spedizione EUR 2,30
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Engineering the Future: AI, Optimization, and the Evolution of Control Systems
Da: California Books, Miami, FL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo I-9798295423116
Compra nuovo
EUR 25,15
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Engineering the Future
Da: PBShop.store US, Wood Dale, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798295423116
Compra nuovo
EUR 31,90
Spedizione gratuita
Spedito in U.S.A.
Spedito in U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Engineering the Future
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
Valutazione del venditore 5 su 5 stelle
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9798295423116
Compra nuovo
EUR 25,81
Spedizione EUR 6,85
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
UNKNOWN
ISBN 13: 9798295423116
Nuovo
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo 51809446-n
Compra nuovo
EUR 25,80
Spedizione EUR 17,50
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
UNKNOWN
ISBN 13: 9798295423116
Antico o usato
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: As New. Unread book in perfect condition. Codice articolo 51809446
Compra usato
EUR 27,50
Spedizione EUR 17,50
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: Più di 20 disponibili
Foto dell'editore
Engineering the Future (Paperback)
Print on DemandDa: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. In an era where engineering systems are growing ever more complex, dynamic, and interconnected, the fusion of artificial intelligence with classical control and optimization is redefining what is possible in automation, robotics, and industrial processes. This work is a sweeping, rigorous, and forward-looking exploration of this transformative landscape, offering both a foundational and practical guide for engineers, researchers, and advanced students seeking to master the next generation of intelligent control systems.The book opens by grounding the reader in the essential principles of optimal control, convex optimization, and system modeling. It revisits the classical paradigms-open-loop and closed-loop control, the calculus of variations, Pontryagin's Minimum Principle, and the Linear Quadratic Regulator (LQR)-not as relics of the past, but as the mathematical bedrock upon which modern AI-augmented strategies are built. Through lucid explanations and illustrative examples, it demonstrates how these time-honored tools remain vital, even as the field pivots toward data-driven and learning-based approaches.A central theme is the seamless integration of machine learning into the control loop. The text delves into system identification from data, showing how neural networks, Gaussian processes, and other learning algorithms can model complex, nonlinear, or poorly understood dynamics-often outperforming traditional analytical models in real-world scenarios. The reader is guided through the nuances of data acquisition, preprocessing, and validation, emphasizing the importance of robust, high-quality datasets for successful learning.The narrative then advances to the cutting edge: reinforcement learning (RL) for control. Here, the book demystifies RL fundamentals, Markov Decision Processes, value-based and policy-based methods, and the emergence of deep RL. It explores how RL agents can learn optimal control policies through interaction, even in the absence of explicit system models, and how these agents can be safely deployed in physical systems through the use of safety layers, constraint handling, and robust verification techniques.Safety and reliability are recurring motifs. The book addresses the critical need for constraint-aware learning, formal verification, and the design of safety shields that guarantee operation within prescribed boundaries-even as controllers adapt and learn online. It presents Model Predictive Control (MPC) as a unifying framework, showing how AI can enhance prediction models, cost functions, and optimization solvers, enabling MPC to tackle previously intractable problems.Industrial case studies-ranging from vehicle control and autonomous driving to wind turbine optimization-bring the theory to life, illustrating the tangible impact of AI-augmented control in practice. Laboratory exercises and implementation guides empower readers to experiment with real hardware and simulation environments, bridging the gap between theory and application.Looking to the horizon, the book surveys future trends: explainable AI in control, lifelong learning, multi-agent systems, quantum computing, and the rise of digital twins. It closes with a thoughtful discussion of ethics, societal impact, and the open problems that will shape the next decade of intelligent automation.Comprehensive yet accessible, is both a roadmap and a manifesto for the future of engineering-where learning, adaptation, and intelligence are at the core of every control system. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798295423116
Compra nuovo
EUR 29,43
Spedizione EUR 43,17
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Engineering the Future : AI, Optimization, and the Evolution of Control Systems
Print on DemandDa: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In an era where engineering systems are growing ever more complex, dynamic, and interconnected, the fusion of artificial intelligence with classical control and optimization is redefining what is possible in automation, robotics, and industrial processes. This work is a sweeping, rigorous, and forward-looking exploration of this transformative landscape, offering both a foundational and practical guide for engineers, researchers, and advanced students seeking to master the next generation of intelligent control systems.The book opens by grounding the reader in the essential principles of optimal control, convex optimization, and system modeling. It revisits the classical paradigms-open-loop and closed-loop control, the calculus of variations, Pontryagin's Minimum Principle, and the Linear Quadratic Regulator (LQR)-not as relics of the past, but as the mathematical bedrock upon which modern AI-augmented strategies are built. Through lucid explanations and illustrative examples, it demonstrates how these time-honored tools remain vital, even as the field pivots toward data-driven and learning-based approaches.A central theme is the seamless integration of machine learning into the control loop. The text delves into system identification from data, showing how neural networks, Gaussian processes, and other learning algorithms can model complex, nonlinear, or poorly understood dynamics-often outperforming traditional analytical models in real-world scenarios. The reader is guided through the nuances of data acquisition, preprocessing, and validation, emphasizing the importance of robust, high-quality datasets for successful learning.The narrative then advances to the cutting edge: reinforcement learning (RL) for control. Here, the book demystifies RL fundamentals, Markov Decision Processes, value-based and policy-based methods, and the emergence of deep RL. It explores how RL agents can learn optimal control policies through interaction, even in the absence of explicit system models, and how these agents can be safely deployed in physical systems through the use of safety layers, constraint handling, and robust verification techniques.Safety and reliability are recurring motifs. The book addresses the critical need for constraint-aware learning, formal verification, and the design of safety shields that guarantee operation within prescribed boundaries-even as controllers adapt and learn online. It presents Model Predictive Control (MPC) as a unifying framework, showing how AI can enhance prediction models, cost functions, and optimization solvers, enabling MPC to tackle previously intractable problems.Industrial case studies-ranging from vehicle control and autonomous driving to wind turbine optimization-bring the theory to life, illustrating the tangible impact of AI-augmented control in practice. Laboratory exercises and implementation guides empower readers to experiment with real hardware and simulation environments, bridging the gap between theory and application.Looking to the horizon, the book surveys future trends: explainable AI in control, lifelong learning, multi-agent systems, quantum computing, and the rise of digital twins. It closes with a thoughtful discussion of ethics, societal impact, and the open problems that will shape the next decade of intelligent automation.Comprehensive yet accessible, is both a roadmap and a manifesto for the future of engineering-where learning, adaptation, and intelligence are at the core of every control system. Codice articolo 9798295423116
Compra nuovo
EUR 59,61
Spedizione EUR 30,50
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili
Immagini fornite dal venditore
Engineering the Future | AI, Optimization, and the Evolution of Control Systems
Print on DemandDa: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Engineering the Future | AI, Optimization, and the Evolution of Control Systems | Ant | Taschenbuch | Englisch | 2025 | Dr. ant | EAN 9798295423116 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Codice articolo 134288218
Compra nuovo
EUR 33,70
Spedizione EUR 70,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 5 disponibili