John N. Hooker

eBook, PDF

Integrated Methods for Optimization (eBook, PDF)

Beschreibung

PEACH (Personal Experience with Active Cultural Heritage) is a large, interdisciplinary development project that explores the use of novel technologies for physical museum visits. Put together by editors and authors who are leading experts on the underlying AI technologies and their application, this book provides a comprehensive survey of the subject. Coverage includes reports on mobile guides, infrastructure and user modeling, the use of stationary devices, collaborative storytelling, 3D modeling, evaluation and usability, and future perspectives. It will be of benefit to AI researchers engaged with interface design as well as practitioners in the area of cultural heritage support and marketing.

Technische Details

• Geräte: PC
• ohne Kopierschutz
• Größe: 4.32MB

Barrierefreiheit

• Text-to-Speech

Autor

John Hooker is a leading researcher in both the Optimization and Constraint Programming research communities. He has been an instrumental principal for this integration, and over the years, he has given numerous presentations and tutorials on the integration of these two areas. It is felt by many in the field that the future Optimization courses will increasingly be taught from this integrated framework.

Prof. Hooker has published two earlier books on the methodologies of Optimization and Constraint Programming. The first was Optimization Methods for Logical Inference (Wiley 1999) and the second was Logic Based Methods for Optimization: Combining Optimization and Constraints Satisfaction (Wiley 2000). This book will be his third book in this evolving area and it is the book that completes the process of integrating these two methodologies into a single set of methods

Produktdetails

• Verlag: Springer US
• Seitenzahl: 486
• Erscheinungstermin: 10. Februar 2007
• Englisch
• ISBN-13: 9780387382746
• Artikelnr.: 43728597

Rezensionen

From the reviews of the second edition: "The book amply illustrates the power of combining the strengths of constraint programming, mathematical programming, global optimization, and heuristics by detailing these approaches, by articulating the commonalties among them, and by applying them to a wide range of optimization problems. ... this book covers the field both broadly and with sufficient granularity to provide working software engineers and graduate students with both a firm theoretical grasp of optimization and the software techniques needed to solve real-world problems. I recommend the book without reservation." (Marlin Thomas, ACM Computing Reviews, July, 2012)