Artificial Intelligence in Real-Time Control 1998. IFAC Proceedings Volumes

  • ID: 1757215
  • Book
  • Elsevier Science and Technology
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This symposium was the seventh in a very successful series in this field. Since the beginning of the series, there have been a number of very positive developments in the topical area of 'Intelligent Control'. In particular, the area referred to as 'situated control' has stimulated the formation of new perspectives towards real-time intelligent systems. The performances of such artificial species as walking cockroaches, maze-negotiating mice, coke-can collecting robots and the like have encouraged the exploration of yet more adaptive control perspectives.

In this symposium, there was a strong wind of change bringing more consideration of the roles of learning, evolution, hybrid systems and so on under many diverse labels and for many different systems and circumstances.

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Chapter headings and selected papers: Architectures for Real-Time Expert Systems. Handling timing in a time-critical reasoning system in a case study (L. Motus). Hybrid Systems. Behavioral programming: enabling a "middle-out" approach to learning and intelligent systems (M.S. Branicky). Evolutionary. How fast can a species adapt and still be evolutionary stable (T.L. Vincent). Real-World Tasks. A study and implementation of intelligent node based on LonWorks technology (Junjie Wang). Special Session on Distributed Control & Panel Discussion. Flow control with electric actuators (C.C. Federspiel). Visualization & Imaging. Spectroscopic imaging sensors in materials process control (J.F. Maguire). Evolutionary. Synthetic optimization approach of combining regional guided order principle and biological evolution strategies and its applications (Chang-Yun Shen). Theoretical Issues & Topics. Compactness of a set of membership functions in L2 space and its application to fuzzy optimal control (Takashi Mitsuishi). Fuzzy or Rough Sets. Predictive control by multiple-step linearization of Takagi-Sugeno fuzzy models (S. Mollov et al.). Framework for approximate time rough control systems an integrated fuzzy sets-rough sets approach (J.F. Peters et al.). Generic Principles and Strategies. Fault-tolerant process control and some future directions (Jianbo Meng). Nonlinear process modeling using a dynamically recurrent neural network (Shi-Rong Liu). Real-World Tasks. Mimicking a fuzzy flight controller using B-splines (A. Aznar Fernández-Montesinos et al.).
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Pao, Y.H.
LeClair, S.R.
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