Skip to main content

Connectionist Propositional Logic A Simple Correlation Matrix Memory Based Reasoning System

  • Chapter
  • First Online:
Emergent Neural Computational Architectures Based on Neuroscience

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2036))

Abstract

A novel purely connectionist implementation of proposi- tional logic is constructed by combining Correlation Matrix Memory operations, tensor products and simple control circuits. The implementa- tion is highly modular and expandable and in its present form it not only allows forward rule chaining but also implements is a hierarchy traversal which results in interesting behavior even in its simplest form.

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

Access this chapter

eBook
USD 16.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. C Orovas J Austin. Cellular associative symbolic processing for pattern recognition. MFCS’ 98 workshop on Grammer Learning, pages 269–280, 1998.

    Google Scholar 

  2. J Austin. Correlation matrix memories for knowledge manipulation. In International Conference on Neural Networks, Fuzzy Logic, and Soft Computing: Iizuka, Japan, 1994.

    Google Scholar 

  3. J Austin. Distributed associative memories for high speed symbolic reasoning. International Journal on Fuzzy Sets and Systems, 82(2):223–233, 1995. Invited paper to the special issue on Connectionist and Hybrid Connectionist Systems for Approximate Reasoning.

    Article  MathSciNet  Google Scholar 

  4. CP Dolan and P Smolensky. Tensor product production system: a modular architecture and representation. Connection Science, (1):53–68, 1989.

    Article  Google Scholar 

  5. JV Kennedy, J Austin, R Pack, and B Cass. C-NNAP: A parallel processing architecture for binary neural networks. In International Conference on Neural Networks (ICANN 95), Perth, Australia, November 1995.

    Google Scholar 

  6. D Kustrin, J Austin, and A Sanders.Application of correlation memory matrices in high frequency asset allocation. In M Niranjan, editor, Fifth International Conference on Artificial Neural Networks. IEE, 1997.

    Google Scholar 

  7. D McDermott. Artificial intelligence meets natural stupidity. SIGART Newsletter, (57), 1976.

    Google Scholar 

  8. S O’Keefe. Neural-Based Content Analysis of Document Images. PhD thesis, Department of Computer Science, University of York, 1997.

    Google Scholar 

  9. M Turner and J Austin. Matching performance of binary correlation matrix memories. Neural Networks, 10(9):1637–1648, 1997.

    Article  Google Scholar 

  10. M Turner and J Austin. A neural network technique for chemical graph matching. In M Niranjan, editor, Proceedings of the Fifth International Conference on Artificial Neural Networks. IEE, 1997.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Kustrin, D., Austin, J. (2001). Connectionist Propositional Logic A Simple Correlation Matrix Memory Based Reasoning System. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_38

Download citation

  • DOI: https://doi.org/10.1007/3-540-44597-8_38

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42363-8

  • Online ISBN: 978-3-540-44597-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics