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Optimal Solutions for Deep and Shallow Engineering Expert Systems

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Applications of Artificial Intelligence in Engineering VI

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Abstract

The paper shows how application of modern graph and network theory to problems of artificial intelligence in engineering can lead to solutions which use fundamental or deep knowledge to provide optimal or near — optimal solutions to significant problems in reasonable computing time. The paper shows implementation in the Prolog language.

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References

  1. Nilsson N. J. “Problem-Solving Methods in Artificial Intellicence”, McGraw Hill, 1971.

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  2. Preiss, K. and Shai O. “Process Planning by Logic Programming”, Robotics and Computer-Integrated Manufacturing, Vol. 5, No. 1, pp 1–10, 1989

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Ben Gurion University, Beer Sheva, Israel

    K. Preiss (The Sir Leon Bagrit Professor of CADCAM) & O. Shai

  2. Pearlstone Center for Aeronautical Engineering Studies, Israel

    K. Preiss (The Sir Leon Bagrit Professor of CADCAM)

Authors
  1. K. Preiss
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  2. O. Shai
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Editor information

Editors and Affiliations

  1. Faculty of Technology, The Open University, Walton Hall, MK7 6AA, Milton Keynes, UK

    G. Rzevski

  2. Computational Mechanics Institute, Wessex Institute of Technology, Ashurst Lodge, SO4 2AA, Ashurst Southampton, UK

    R. A. Adey

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© 1991 Computational Mechanics Publications

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Preiss, K., Shai, O. (1991). Optimal Solutions for Deep and Shallow Engineering Expert Systems. In: Rzevski, G., Adey, R.A. (eds) Applications of Artificial Intelligence in Engineering VI. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-3648-8_61

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  • DOI: https://doi.org/10.1007/978-94-011-3648-8_61

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-85166-678-2

  • Online ISBN: 978-94-011-3648-8

  • eBook Packages: Springer Book Archive

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