Skip to main content

Universal Principles of Measurement and Language Functions in Evolving Systems

  • Chapter
Facets of Systems Science

Abstract

The ability to construct measuring devices and to predict the results of measurements using models expressed in formal mathematical language is now generally accepted as the minimum requirement for any form of scientific theory. The modern cultural development of these skills is usually credited to the Newtonian epoch, although traces go back at least 2000 years to the Milesian philosophers. In any case, from the enormously broader evolutionary perspective, covering well over three billion years, the inventions of measurement and language are commonly regarded as only the most recent and elaborate form of intelligent activity of the most recent and elaborate species.

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 149.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Barto, A. (1984). Simulation Experiments with Goal-seeking Adaptive Elements. Final Report, June 1980—August 1983 (Avionics Lab., Air Force Wright Aeronautical Lab, Wright-Patterson Air Force Base, Ohio 45433 ).

    Google Scholar 

  • Bremermann, H. J. (1962). Optimization through evolution and recombination, in M. C. Yovits, G. T.

    Google Scholar 

  • Jacobi, and G. D. Goldstein (Eds.) Self-Organizing Systems (Washington, DC: Spartan Books).

    Google Scholar 

  • Conrad, M. and Hastings, H. M. (1985). Scale change and the emergence of information processing primitives. J. Theoret. Biol. (in press).

    Google Scholar 

  • Conrad, M. and Pattee, H. H. (1970). Evolution experiments with an artificial ecosystem. J. Theoret. Biol. 28: 393–409.

    Article  Google Scholar 

  • Eigen, M. and Schuster, P. (1979). The Hypercycle: A Principle of Natural Self-Organization (Heidelberg, Berlin, New York: Springer).

    Google Scholar 

  • Fogel, L. J., Owens, A. J., and Walsh, M. J. (1966). Artificial Intelligence Through Simulated Evolution ( New York: Wiley).

    Google Scholar 

  • Gibson, J. J. (1979). The Ecological Approach to Visual Perception ( Boston: Houghton-Mifflin).

    Google Scholar 

  • Haken, H. (1981). Synergetics: is self-organization governed by universal principles?, in E. Jantsch (Ed.) The Evolutionary Vision. AAAS Selected Symposium 61 ( Boulder, CO: Westview Press ).

    Google Scholar 

  • Hockett, E. (1966). The problem of universals in language, in J. H. Greenberg (Ed.) Universals of Language ( Cambridge: MIT Press ) pp. 1–29.

    Google Scholar 

  • Holland, J. (1975). Adaptation in Natural and Artificial Systems ( Ann Arbor, MI: Michigan University Press).

    Google Scholar 

  • Klopf, A. H. and Gose, E. (1969). An evolutionary pattern recognition network, IEEE Pans. of Systems Science and Cybernetics 5: 247–50.

    Article  Google Scholar 

  • Moorehead, P S. and Kaplan, M. M. (Eds.) (1967). Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution ( Philadelphia: The Wistar Institute Press ).

    Google Scholar 

  • Nagel, E. (1932). Measurement. Reprinted in Danto, A. and Morganbesser, S. (1960). Philosophy of Science ( New York: World Publishing Co.).

    Google Scholar 

  • von Neumann, J. (1966). Theory of Self-Reproducing Automata. Edited and completed by A. W. Burks ( Urbana, IL: University of Illinois Press).

    Google Scholar 

  • Newell, A. (1980). Physical symbol systems, Cognitive Science 4: 135–83.

    Article  Google Scholar 

  • Pattee, H. (1972a). The nature of hierarchical controls in living matter, in R. Rosen (Ed.) Foundations of Mathematical Biology, Vol. 1 ( New York: Academic Press ) pp. 1–22.

    Google Scholar 

  • Pattee, H. (1972b). Physical problems of decision-making constraints. Int. J. Neuroscience 3: 99–106.

    Article  Google Scholar 

  • Pattee, H. (1982). Cell psychology: an evolutionary approach to the symbol-matter problem. Cognition and Brain Theory 5 (4): 325–341.

    Google Scholar 

  • Polanyi, M. (1968). Life’s irreducible structure. Science 160: 1308–1312.

    Article  Google Scholar 

  • Prigogine, J. (1980). From Being to Becoming: Time and Complexity in the Physical Sciences ( San Francisco: W. H. Freeman & Co).

    Google Scholar 

  • Pylyshyn, Z. (1980). Computation and cognition: issues in the foundations of cognitive science. The Behavioral and Brain Sciences 3: 111–169.

    Article  Google Scholar 

  • Thom, R. (1975). Structural Stability and Morphogenesis ( Reading, MA: W. A. Benjamin).

    Google Scholar 

  • Tùrvey, M. and Carello, C. (1981). Cognition: the view from ecological realism. Cognition 10: 313–321.

    Article  Google Scholar 

  • Tùrvey, M. and Kugler, P. (1984). An ecological approach to perception and action, in H.T.A. Whiting (Ed.) Human Motor Actions: Burnstein Reassessed ( Amsterdam: North-Holland Publishing Co ).

    Google Scholar 

  • Waddington, C. H. (1968). The basic ideas of biology, in C. H. Waddington (Ed.) Towards a Theoretical Biology I. Prolegomena ( Edinburgh: Edinburgh University Press ) pp. 1–32.

    Google Scholar 

Download references

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer Science+Business Media New York

About this chapter

Cite this chapter

Pattee, H.H. (1991). Universal Principles of Measurement and Language Functions in Evolving Systems. In: Facets of Systems Science. International Federation for Systems Research International Series on Systems Science and Engineering, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-0718-9_42

Download citation

  • DOI: https://doi.org/10.1007/978-1-4899-0718-9_42

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4899-0720-2

  • Online ISBN: 978-1-4899-0718-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics