The book presents powerful optimization approaches for integrating AI into daily life.
This book explores how heuristic and metaheuristic methodologies have revolutionized the fields of robotics and machine learning. The book covers the wide range of tools and methods that have emerged as part of the AI revolution, from state-of-the-art decision-making algorithms for robots to data-driven machine learning models. Each chapter offers a meticulous examination of the theoretical foundations and practical applications of mathematical optimization, helping readers understand how these methods are transforming the field of technology.
This book is an invaluable resource for researchers, practitioners, and students. It makes AI optimization accessible and comprehensible, equipping the next generation of innovators with the knowledge and skills to further advance robotics and machine learning. While artificial intelligence constantly evolves, this book sheds light on the path ahead.
This book explores how heuristic and metaheuristic methodologies have revolutionized the fields of robotics and machine learning. The book covers the wide range of tools and methods that have emerged as part of the AI revolution, from state-of-the-art decision-making algorithms for robots to data-driven machine learning models. Each chapter offers a meticulous examination of the theoretical foundations and practical applications of mathematical optimization, helping readers understand how these methods are transforming the field of technology.
This book is an invaluable resource for researchers, practitioners, and students. It makes AI optimization accessible and comprehensible, equipping the next generation of innovators with the knowledge and skills to further advance robotics and machine learning. While artificial intelligence constantly evolves, this book sheds light on the path ahead.
Produkteigenschaften
- Artikelnummer: 9783111436050
- Medium: Buch
- ISBN: 978-3-11-143605-0
- Verlag: De Gruyter
- Erscheinungstermin: 27.03.2025
- Sprache(n): Englisch
- Auflage: 1. Auflage 2025
- Serie: ISSN
- Produktform: Gebunden
- Seiten: 250
- Format (B x H): 170 x 240 mm
- Ausgabetyp: Kein, Unbekannt
Themen
- Wirtschaftswissenschaften
- Wirtschaftssektoren & Branchen
- Medien-, Informations und Kommunikationswirtschaft
- Informationstechnik, IT-Industrie
- Mathematik | Informatik
- Mathematik
- Numerik und Wissenschaftliches Rechnen
- Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik
- EDV | Informatik
- Informatik
- Künstliche Intelligenz
- Mustererkennung, Biometrik
- Technische Wissenschaften
- Sonstige Technologien | Angewandte Technik
- Medizintechnik, Biomedizintechnik