A Dynamical Approach to Identity and Diversity in Complex Systems

Chapter
Part of the Issues in Business Ethics book series (IBET, volume 26)

Abstract

The subject of this chapter is the identity of individual dynamical objects and properties. Two problems have dominated the literature: trans-temporal identity and the relation between composition and identity. Most traditional approaches to identity rely on some version of classification via essential or typical properties, whether nominal or real. Nominal properties have the disadvantage of producing unnatural classifications, and have several other problems. Real properties, however, are often inaccessible or hard to define (strict definition would make them nominal). I suggest that classification should be in terms of dynamical properties of systems, starting with individual systems rather than classes, and working up by abstractions that fit causal generalities. The advantage of this approach is that individuality is testable and revisable as we come to know more about systems. Another advantage is that if anything is real, then it is the dynamical. Once I have presented this approach in general, I will show that the central concept of dynamical cohesion (the “dividing glue”) is amenable to giving a principled account of individuation as a process, at the same time explaining the origin of diversity. Some other advantages of this approach are presented, including how it can be used as a basis for testable classifications. This last has moral implications, since cohesion at the individual and the social levels, and their interactions, can impinge on proper moral decisions.

Keywords

Equivalence Relation Entropy Production Identity Relation Unity Relation Modal Identity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Andresen, B., Shiner, J.S., and Uehlinger, D.E. 2002. Allometric scaling and maximum efficiency in physiological eigen time. DOI:10.1073/pnas.082633699.Google Scholar
  2. Brooks, D.R. and Wiley, E.O. 1988. Evolution as entropy (2nd Ed.). Chicago, IL: University of Chicago Press.Google Scholar
  3. Collier, J. 1986. Entropy in evolution. Biology and Philosophy, 1: 5–24.CrossRefGoogle Scholar
  4. Collier, J. 1988. Supervenience and reduction in biological hierarchies. In M. Matthen and B. Linsky (eds.). Philosophy and Biology: Canadian Journal of Philosophy Supplementary, 14: 209–234.Google Scholar
  5. Collier, J. 1996. Information originates in symmetry breaking. Symmetry: Culture & Science, 7: 247–256.Google Scholar
  6. Collier, J. 1999. Autonomy in anticipatory systems: Significance for functionality, intentionality and meaning. In D.M. Dubois (ed.), Computing anticipatory systems, CASYS’98 – second international conference, American Institute of Physics, Woodbury, New York, AIP Conference Proceedings 465, pp. 75–81.CrossRefGoogle Scholar
  7. Collier, J. 2000. Autonomy and process closure as the basis for functionality. In J.L.R Chandler, and G. van de Vijver (eds.), Closure: Emergent organizations and their dynamics, Annals of the New York Academy of Science, 901: 280–291, Published by Wiley Interscience.Google Scholar
  8. Collier, J. 2001. Dealing with the unexpected. In Partial proceedings of CASYS 2000: Fourth international conference on computing anticipatory systems, International Journal of Computing Anticipatory Systems, 10: 21–30, published by CHAOS.Google Scholar
  9. Collier, J. 2002. What is autonomy? In Partial proceedings of CASYS’01: Fifth international conference on computing anticipatory systems, International Journal of Computing Anticipatory Systems, 12, pp. 212–221, published by CHAOS.Google Scholar
  10. Collier, J. 2003. Hierarchical dynamical information systems with a focus on biology. Entropy, 5: 100–124.CrossRefGoogle Scholar
  11. Collier, J. 2004a. Self-organization, individuation and identity. Revue Internationale de Philosophie, 59: 151–172.Google Scholar
  12. Collier, J. 2004b. Autonomy, anticipation and novel adaptations. In I. Dubranova (ed.), Science of self-organization and self-organization of science. Kyiv: Abris, pp. 64–89.Google Scholar
  13. Collier, J. 2004c. Reduction, supervenience, and physical emergence. Behavioral and Brain Sciences, 27 (5): 629–630.CrossRefGoogle Scholar
  14. Collier, J. 2006. Conditions for fully autonomous anticipation. In D.M. Dubois (ed.), Computing Anticipatory Systems: CASY’05 – Sixth International Conference, American Institute of Physics, Melville, New York, AIP Conference Proceedings 839, pp. 282–289.Google Scholar
  15. Collier, J. 2008a. Simulating autonomous anticipation: The importance of Dubois’ conjecture. BioSystems, 91: 346–354.CrossRefGoogle Scholar
  16. Collier, J. 2008b. A dynamical account of emergence. Cybernetics and Human Knowing, 15 (3–4): 5–14.Google Scholar
  17. Cumming, G.S. and Collier, J. 2005. Change and identity in complex systems. Ecology and Society, 10 (1): 29. [online] URL: http://www.ecologyandsociety.org/vol10/iss1/art29/
  18. Collier, J. and Cumming, G.S. (forthcoming 2011). A dynamical approach to ecosystem identity. In B. Brown, K. deLaplante and K. Peacock (Eds.). Philosophy of Ecology. Dordrecht: North-Holland.Google Scholar
  19. Collier, J. and Hooker, C.A. 1999. Complexly organised dynamical systems. Open Systems and Information Dynamics, 6: 241–302.CrossRefGoogle Scholar
  20. Dewar, R. 2003. Information theory explanation of the fluctuation theorem, maximum entropy production and self-organized criticality in non-equilibrium stationary states. Journal of Physics A: Mathematical and General, 36: 631–641.CrossRefGoogle Scholar
  21. Frautschi, S. 1982. Entropy in an expanding universe. Science, 217: 593–599.CrossRefGoogle Scholar
  22. Fuchs, C. and John C. 2007. A dynamic systems view of economic and political theory. Theoria, 113: 23–52.CrossRefGoogle Scholar
  23. Hill, A. 1990. Entropy production as the selection rule between different growth morphologies. Nature, 348: 426–428.CrossRefGoogle Scholar
  24. Hooker, C.A. 2004. Asymptotics, reduction and emergence. British Journal for the Philosophy of Science, 55: 435–479.CrossRefGoogle Scholar
  25. Kauffman, S.A. 1985. Self-organisation, selective adaptation, and its limits. In D. Depew, B. Weber (eds.), Evolution at a crossroads: The new biology and the new philosophy of science. Cambridge, MA: MIT Press.Google Scholar
  26. Kauffman, S.A. 1991. Antichaos and adaptation. Scientific American, 265: 64–70.CrossRefGoogle Scholar
  27. Kauffman, S.A. 1993. Origins of order: Self-organisation and selection in evolution. New York: Oxford University Press.Google Scholar
  28. Landsberg, P.T. 1984. Can entropy and ‘order’ increase together? Physics Letters, 102a: 171–173.Google Scholar
  29. Layzer, D. 1990. Cosmogenesis. Oxford, Oxfordshire: Oxford University Press.Google Scholar
  30. Locke, J. 1690. An essay concerning human understanding. London: William Tyler.Google Scholar
  31. Lorenz, R.D. 2002. Planets, life and the production of entropy. International Journal of Astrobiology, 1: 3–13.CrossRefGoogle Scholar
  32. Mahulikar, S.P. and Herwig, H. 2008. Exact thermodynamic principles for dynamic order existence and evolution of chaos. Chaos, Solitions and Fractals, 38. DOI: 10.1016/j.chaos.2008.07.051.Google Scholar
  33. Muller, S.J. 2007. Asymmetry: The foundation of information. Berlin: Springer-Verlag.Google Scholar
  34. Nicolis, G., Dewel, G., Turner, J.W. 1981. Order and fluctuations in equilibrium and nonequilibrium statistical mechanics. New York: Wiley.Google Scholar
  35. Perry, J. 2002. Identity, personal identity, and the self. Indianapolis, IN: Hackett.Google Scholar
  36. Rosen, R. 1991. Life itself. New York: Columbia University Press.Google Scholar
  37. Rosen, R. 2000. Essays on life itself. New York: Columbia University Press.Google Scholar
  38. Salthe, S.N. 1993. Development and evolution. Complexity and change in biology. Cambridge, MA: MIT Press.Google Scholar
  39. von Foerster, H. 1960. On self-organizing systems and their environments. In M.C.Yovits and S. Cameron (eds.), Self-organizing systems. London: Pergamon Press.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.School of Philosophy and EthicsUniversity of KwaZulu-NatalDurbanSouth Africa

Personalised recommendations