Skip to main content

The Complex Cognitive Systems Manifesto

  • Chapter
  • First Online:
Nanotechnology, the Brain, and the Future

Part of the book series: Yearbook of Nanotechnology in Society ((YNTS,volume 3))

  • 1919 Accesses

Abstract

In a complex system the overall behavior of the system cannot be analytically explained in terms of the underlying mechanism that causes the behavior. This paper argues that the human cognitive system is almost certainly a partial complex system, and that one consequence of this complexity is that if we try to understand human cognition by looking only for the locally-most-optimal models of all aspects of the system, we will generate models that can never converge on a unified theory. This has serious implications for the methodology of cognitive science. To solve this “complex systems problem,” it is proposed that researchers move toward a new, more theoretically intensive research paradigm that shifts the focus away from local models and toward parameterized “generators” of large sets of models. These generators would then be organized using frameworks, each of which is a prototype of a unified theory of cognition, and the research methodology would involve constraint relaxation among the generated models. The paper concludes with a description of a specific framework, based on a generalized version of connectionism, and the suggestion that this new methodology can only be realized if a new class of software tools is built to support it.

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

Access this chapter

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 EPUB and 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
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  • Ackley, D.H., G.E. Hinton, and T.J. Sejnowski. 1985. A learning algorithm for Boltzmann machines. Cognitive Science 9: 147–169.

    Article  Google Scholar 

  • Bruce V., and A. Young. 1986. Understanding face recognition. British Journal of Psychology 77(Pt 3): 305–327.

    Article  Google Scholar 

  • Gardner, M. 1970. Mathematical games: The fantastic combinations of John Conway’s new ­solitaire game ‘life’. Scientific American 223(4): 120–123.

    Article  Google Scholar 

  • Horgan, J. 1995. From complexity to perplexity. Scientific American 272(6): 104–109.

    Article  Google Scholar 

  • Kuhn, T.S. 1962. The structure of scientific revolutions. Chicago: University of Chicago Press.

    Google Scholar 

  • Loosemore, R.P.W., and T.A. Harley. 2010. Brains and minds: On the usefulness of localisation data to cognitive psychology. In Foundational issues of neuroimaging, ed. M. Bunzl and S.J. Hanson. Cambridge, MA: MIT Press.

    Google Scholar 

  • Marslen-Wilson, W.D. 1990. Activation, competition, and frequency in lexical access. In Cognitive models of speech processing: Psycholinguistics and computational perspectives, ed. G.T.M. Altmann, 148–172. Cambridge, MA: MIT Press.

    Google Scholar 

  • McClelland, J.L., and D.E. Rumelhart. 1981. An interactive activation model of context effects in letter perception: Part 1. An account of basic findings. Psychological Review 88: 375–407.

    Article  Google Scholar 

  • McClelland, J.L., D.E. Rumelhart, and The PDP Research Group. 1986a. Parallel distributed ­processing: Explorations in the microstructure of cognition, Psychological and biological ­models, vol. 2. Cambridge, MA: MIT Press.

    Google Scholar 

  • McClelland, J.L., D.E. Rumelhart, and G.E. Hinton. 1986b. The appeal of parallel distributed processing. In Parallel distributed processing: Explorations in the microstructure of cognition, vol. 1, ed. D.E. Rumelhart, J.L. McClelland, and The PDP Research Group. Cambridge, MA: MIT Press.

    Google Scholar 

  • Mitchell, M. 2008. Complexity: A guided tour. New York: Oxford University Press.

    Google Scholar 

  • Rumelhart, David E., D.E. Rumelhart, G.E. Hinton, and R.J. Williams. 1986a. Learning representations by back-propagating errors. Nature 323: 533–536.

    Article  Google Scholar 

  • Rumelhart, D.E., J.L. McClelland, and The PDP Research Group. 1986b. Parallel distributed ­processing: Explorations in the microstructure of cognition, Foundations, vol. 1. Cambridge, MA: MIT Press.

    Google Scholar 

  • Waldrop, M.M. 1992. Complexity: The emerging science at the edge of order and chaos. New York: Simon & Schuster.

    Google Scholar 

  • Wolfram, S. 2002. A new kind of science, 737–750. Champaign: Wolfram Media.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Richard P. W. Loosemore .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Loosemore, R.P.W. (2013). The Complex Cognitive Systems Manifesto. In: Hays, S., Robert, J., Miller, C., Bennett, I. (eds) Nanotechnology, the Brain, and the Future. Yearbook of Nanotechnology in Society, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1787-9_12

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-1787-9_12

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-1786-2

  • Online ISBN: 978-94-007-1787-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics