Riassunto
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. This text 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 and knowledge-based scheduling systems. Readers should be able to save considerable time in searching the scattered literature in the field, and should find here a set of how-to-do issues and results which should improve their skills in analyzing and designing AI-based systems.
Contenuti
Preface. Part 1: General Issues. 1. Artificial Intelligence in Industrial Decision Making, Control and Automation: an Introduction; S.G. Tzafestas, H. Verbruggen. 2. Conceptual integration of Qualitative and Quantitative Process Models; E.A. Woods. 3. Timing Problems and their Handling at System Integration; L. Motus. 4. Analysis for Correct Reasoning in Interactive Man Robot Systems: Disjunctive Syllogism with Modus ponens and Modus tollens; E.C. Koenig. Part 2: Intelligent Systems. 5. Applied Intelligent Control Systems: R. Shoureshi, M. Wheeler, L. Brackney. 6. Intelligent Simulation in Designing Complex Dynamic Control Systems; F. Zhao. 7. Multiresolutional Architectures for Autonomous Systems with Incomplete and Indequate Knowledge Representation; A. Meysel. 8. Distributed Intelligent Systems in Cellular Robotics; T. Fuikuda, T. Ueyama, K. Sekiyama. 9. Distributed Artificial Intelligence in Manufacturing Control; S. Albayrak, H. Krallmann. Part 3: Neural Networks in Modelling, Control and Scheduling. 10. Artificial Neural Networks for Modelling; A.J. Krijgsman, H.B. Verbruggen, P.M. Bruijn. 11. Neural Networks in Robot Control; S.G. Tzafestas. 12. Control Strategy of Robotic Manipulator Based on Flexible Neural Network Structure; M. Teshnehlab, K. Watanabe. 13. Neuro-Fuzzy Approaches to Anticipatory Control; L.H. Tsoukalas, A. Ikonomopoulos, R.E. Uhrig. 14. New Approaches to Large-Scale Scheduling Problems: Constraint Directed Programming and Neural Networks; Y. Kobayashi, N. Nonaka. Part 4: Systems Diagnostics. 15. Knowledge-Based Fault Diagnosis of Technological Systems; H.B. Verbruggen, S.G. Tzafestas, E. Zanni. 16. Model-Based Diagnosis: State Transition Events and Constraint Equations; K.-E. Arzen, A. Wallen, T.F. Petti. 17. Diagnosis with Explicit Models of Goals and Functions; J.E. Larsson. Part 5: Industrial Robotic, Manufacturing and Organizational Systems. 18. Multi-Sensor Integration for Mobile Robot Navigation; A. Traca de Almeida, H. Araujo, J. Dias, U. Nunes. 19. Incremental Design of a Flexible Robotic Assembly Cell Using Reactive Robots; E.s. Tzafestas, S.G. Tzafestas. 20. On the Comparison of AI and DAI Based Planning Techniques for Automated Manufacturing Systems; A.I. Kokkinaki, K.P. Valavanis. 21. Knowledge-Based Supervision of Flexible Manufacturing Systems; A.K.A. Toguyeni, E. Craye, J.-C. Gentina. 22. A Survey of Knowledge-Based Industrial Scheduling; K.S. Hindi, M.g. Singh. 23. Reactive Batch Scheduling; V.J. Terpstra, H.B. Verbruggen. 24. Applying Groupware Technologies to Support Management in Organizations; A. Michailidis, P.-I. Gouma, R. Rada. Index.
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