Skip to main content

H

  • Chapter

Part of the book series: Symbolic Computation ((1064))

Abstract

In a pipelined <172> or hierarchical process Organisation, data passes through a sequence of analytical or interpretive modules each of which acts independently of the rest. In a heterarchical system, modules may invoke other modules in the series to help with e.g. disambiguation of data. Winograd’s program SHRDLU, in which syntactic analysis could make use of semantic modules on knowledge about the world was the most famous example. Shirai and others designed heterarchic image understanding programs. Heterarchy fell into disrepute when the work of Horn, Barrow and Tenenbaum suggested that far more disambiguation can be done autonomously by low levels than was previously thought. The fashion will change again when it is realised that in poor viewing conditions more sophisticated process Organisation is required.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Clowes, M.B. Man the creative machine. In J. Benthall, editor, The limits of human nature. Allen Lane, London, 1973

    Google Scholar 

  • Nilsson, N.J. Principles of Artificial Intelligence. Tioga Pub. Co., San Mateo, California, 1980.

    MATH  Google Scholar 

  • Brooks, R.A. Symbolic reasoning among 3D models and 2D images. Artificial Intelligence, 17(1): 285–349, 1981.

    Article  Google Scholar 

  • Sacerdoti, E.D. Planning in a hierarchy of abstraction Spaces. Artificial Intelligence, 5:115–135, 1978.

    Article  Google Scholar 

  • Tate, A. Generating project networks. In Proceedings of IJCAI-77, pages 888–893, International Joint Conference on Artificial Intelligence, 1977.

    Google Scholar 

  • Barstow, D.R. An experiment in knowledge-based automatic programming. Artificial Intelligence, 12:73–119, 1979.

    Article  Google Scholar 

  • Fisher, R. B. From Surfaces to Objects: Computer Vision and Three Dimensional Scene Analysis. John Wiley and Sons, Chichester, 1989.

    Google Scholar 

  • Cohen, P.R. and Feigenbaum, E.A. (editors). The Handbook of Artificial Intelligence, Volume 3, pages 206–215. Pitman, London, 1982.

    MATH  Google Scholar 

  • Pearl, J. Heuristics: intelligent search strategies for Computer problem solving, pages 35–36. Addison-Wesley, Reading, Mass. and London, 1984.

    Google Scholar 

  • Hough, P.V.C. Method and Means for Recognising Complex Patterns. U.S. Patent 3,069,654, 1962

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1990 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Bundy, A. (1990). H. In: Bundy, A. (eds) Catalogue of Artificial Intelligence Techniques. Symbolic Computation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-97276-8_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-97276-8_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-97278-2

  • Online ISBN: 978-3-642-97276-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics