A Missing Link in Cybernetics

Logic and Continuity

  • Authors
  • Alex M. Andrew
Part of the IFSR International Series on Systems Science and Engineering book series (IFSR, volume 26)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Alex M. Andrew
    Pages 1-16
  3. Alex M. Andrew
    Pages 17-36
  4. Alex M. Andrew
    Pages 37-55
  5. Alex M. Andrew
    Pages 57-83
  6. Alex M. Andrew
    Pages 85-104
  7. Alex M. Andrew
    Pages 105-111
  8. Alex M. Andrew
    Pages 113-116
  9. Alex M. Andrew
    Pages 117-126
  10. Back Matter
    Pages 127-139

About this book

Introduction

The relative failure of attempts to analyze and model intelligence can be attributed in part to the customary assumption that the processing of continuous variables and the manipulation of discrete concepts should be treated separately. In this book, the author considers concept-based thought as having evolved from processing of continuous variables. Although "fuzzy" theory acknowledges the need to combine conceptual and continuous processing, its assumption of the primacy of concept-based processing makes it evolutionarily implausible.

The text begins by reviewing the origins and aims of cybernetics with particular reference to Warren McCulloch’s declared lifetime quest of "understanding man’s understanding". It is shown that continuous systems can undergo complex self-organization, but a need for classification of situations becomes apparent and can be seen as the evolutionary beginning of concept-based processing. Possibilities for complex self-organization are emphasized by discussion of a general principle that has been termed significance feedback, of which backpropagation of errors in neural nets is a special case.

It is also noted that continuous measures come to be associated with processing that is essentially concept-based, as acknowledged in Marvin Minsky’s reference to heuristic connection between problems, and the associated basic learning heuristic of Minsky and Selfridge. This reappearance of continuity, along with observations on the multi-layer structure of intelligent systems, supports a potentially valuable view of intelligence as having a fractal nature. This is such that structures at a complex level, interpreted in terms of these emergent measures, reflect others at a simpler level. Implications for neuroscience and Artificial Intelligence are also examined.

The book presents unconventional and challenging viewpoints that will be of interest to researchers in AI, psychology, cybernetics and systems science, and should help promote further research.

Keywords

Backpropagation Evolution Marvin Minsky articifical intelligence artificial intelligence classification cybernetics intelligence intelligent systems knowledge learning linear optimization

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-75164-1
  • Copyright Information Springer-Verlag New York 2009
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-75163-4
  • Online ISBN 978-0-387-75164-1
  • Series Print ISSN 1574-0463
  • About this book