Software Engineering, Artificial Intelligence and Expert Systems for High Energy and Nuclear Physics: Proceedings of the Second International Workshop

Software Engineering, Artificial Intelligence and Expert Systems for High Energy and Nuclear Physics: Proceedings of the Second International Workshop

By: D.Perret- Gallix (editor)Hardback

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An example of the growing need for frontier physics experiments to make use of frontier technology is in the field of Artificial Intelligence (AI) and related themes. By AI we are referring here to the use of computers to deal with complex objects in an environment based on specific rules (symbolic manipulation); to assist groups of developers in the design, coding and maintenance of large packages (software engineering); to mimic human reasoning and strategy with knowledge bases to make a diagnosis of equipment (expert systems) or to implement a model of the brain to solve pattern recognition problems (neural networks). These techniques, developed some time ago by AI researchers, are confronted by down-to-earth problems arising in high-energy and nuclear physics. However, similar situations exist in other "big sciences" such as space research or plasma physics, and common solutions can be applied. The magnitude and complexity of the experiments on the horizon for the end of the century clearly call for the application of AI techniques. Solutions are sought through international collaboration between research and industry.


The logic of method components, C. Vogel; expertise with mixed language programming, M. Kunze; experience with the object oriented approach for the new Delphi on-line event display, Ch. Arnault; software tools for transputer networks, G Gingrich; SLAC B-factory computing, P. Kunz; evolutionary algorithms - some very old strategies for optimization and adaptation, Th. Back; neural networks for pattern recognition, F. Fogelman-Soulie; network applications in high energy physics, B. Denby; neural network in high energy physics, algorithms and results, C. Peterson; microelectronics for neural networks, D. Seligson; the need for neural networks at LHC and SSC, J.R. Hansen; event reconstruction using embedded expert systems, G. King; distributed co-operative architecture for accelerator operation, J. Fuchs; safety on high energy physics experiments by an expert system, F. Chevier; which Feynman diagrams are algebraically computable?, D. Broadhurst; techniques for the automatic manipulation of amplitudes and loops, J. Verm; grace and channel, automatic calculation of cross sections, T. Kaneko; compHEP integrated system for automatic calculations in HEP, S. Shichanin; computer algebraic generation and calculation of Feynman graphs using FeyA and FeynCalc, H. Eck; symbolic high-energy physics calculations using maple, E. Yehuda.

Product Details

  • ISBN13: 9789810211226
  • Format: Hardback
  • Number Of Pages: 800
  • ID: 9789810211226
  • ISBN10: 9810211228

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