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.