Artificial Intelligence in Industrial Decision Making, Control and Automation (Intelligent Systems, Control and Automation: Science and Engineering, 14)

ISBN 10: 9401041342 / ISBN 13: 9789401041348

Verlag: Springer, 2012

Beschreibung

Bestandsnummer des Verkäufers ABLIING23Apr0412070054329

Bibliografische Details

• Titel: Artificial Intelligence in Industrial Decision Making, Control and Automation (Intelligent Systems, Control and Automation: Science and Engineering, 14)
• Verlag: Springer
• Erscheinungsjahr: 2012
• Sprache: Englisch
• ISBN-10: 9401041342
• ISBN-13: 9789401041348
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

The field of artificial intelligence (Ai) has expanded enormously during the last years, and solid theoretical and application results are now available. Researchers and practitioners are building Ai-based systems that face real-world and industrial problems. Artificial Intelligence in Industrial Decision Making, Control and Automation provides a balanced state-of-the-art presentation of the involvement of Ai in the design and operation of important industrial systems with built-in intelligence. Topics included are: integration of qualitative and quantitative models, timing problems, intelligent simulation and control, multiresolutional architectures for autonomous systems, Dai systems, artificial neural networks in modelling and control, system diagnostics, industrial robotic systems and cells, man-robot systems, flexible manufacturing systems, knowledge-based scheduling systems.
Readers can save considerable time in searching the scattered literature in the field, and can find here a rich set of how-to-do issues and results which will improve their skills in analyzing and designing Ai-based systems.

Reseña del editor

This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems.